* 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_19_01_50_00_654/RtmpUTYrc8/R.INSTALL1a7b45f1514b6/blavaan/src' g++ -std=gnu++17 -I"D:/RCompile/recent/R-4.5.1/include" -DNDEBUG -I"../inst/include" -I"D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include' -I'D:/RCompile/CRANpkg/lib/4.5/rstan/include' -I'D:/RCompile/CRANpkg/lib/4.5/BH/include' -I'D:/RCompile/CRANpkg/lib/4.5/Rcpp/include' -I'D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include' -I'D:/RCompile/CRANpkg/lib/4.5/RcppParallel/include' -I"d:/rtools45/x86_64-w64-mingw32.static.posix/include" -DRCPP_PARALLEL_USE_TBB=1 -I"D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/Core:205, from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Dense:1, from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/RcppEigenForward.h:28, from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/RcppEigen.h:25, from RcppExports.cpp:4: D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/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/4.5/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/4.5/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 { | ^ D:/RCompile/CRANpkg/lib/4.5/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 { | ^ D:/RCompile/CRANpkg/lib/4.5/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& kernel) { | ^ D:/RCompile/CRANpkg/lib/4.5/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& kernel) { | ^ In file included from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Core:174: D:/RCompile/CRANpkg/lib/4.5/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 { \ | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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 { \ | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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 { \ | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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 { \ | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/Core:165: D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits >' 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from 'struct Eigen::internal::traits >' 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:24:46: required from here 24 | ResAlignment = traits >::Alignment | ^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128'} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Core:271: D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix' 178 | class Matrix | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from 'class Eigen::QuaternionBase >' 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from 'class Eigen::Quaternion' 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:27:3: required from here 27 | { | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits >' 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from 'struct Eigen::internal::traits >' 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:98:47: required from here 98 | ResAlignment = traits >::Alignment | ^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix' 178 | class Matrix | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from 'class Eigen::QuaternionBase >' 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from 'class Eigen::Quaternion' 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:102:3: required from here 102 | { | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/SparseCore:37, from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Sparse:26, from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/RcppEigenForward.h:29: D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of 'class Eigen::SparseMatrixBase >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from 'class Eigen::SparseCompressedBase >' 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMatrix.h:96:7: required from 'class Eigen::SparseMatrix' 96 | class SparseMatrix | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h:61:25: required from here 61 | typedef Triplet T; | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ g++ -std=gnu++17 -I"D:/RCompile/recent/R-4.5.1/include" -DNDEBUG -I"../inst/include" -I"D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include' -I'D:/RCompile/CRANpkg/lib/4.5/rstan/include' -I'D:/RCompile/CRANpkg/lib/4.5/BH/include' -I'D:/RCompile/CRANpkg/lib/4.5/Rcpp/include' -I'D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include' -I'D:/RCompile/CRANpkg/lib/4.5/RcppParallel/include' -I"d:/rtools45/x86_64-w64-mingw32.static.posix/include" -DRCPP_PARALLEL_USE_TBB=1 -I"D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/Core:205, from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Dense:1, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:22, from D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/rstaninc.hpp:3, from stanExports_stanmarg.h:23, from stanExports_stanmarg.cc:5: D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/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/4.5/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/4.5/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 { | ^ D:/RCompile/CRANpkg/lib/4.5/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 { | ^ D:/RCompile/CRANpkg/lib/4.5/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& kernel) { | ^ D:/RCompile/CRANpkg/lib/4.5/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& kernel) { | ^ In file included from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Core:174: D:/RCompile/CRANpkg/lib/4.5/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 { \ | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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 { \ | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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 { \ | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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 { \ | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/Core:165: D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits >' 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from 'struct Eigen::internal::traits >' 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:24:46: required from here 24 | ResAlignment = traits >::Alignment | ^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128'} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Core:271: D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix' 178 | class Matrix | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from 'class Eigen::QuaternionBase >' 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from 'class Eigen::Quaternion' 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:27:3: required from here 27 | { | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits >' 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:266:49: required from 'struct Eigen::internal::traits >' 266 | Alignment = internal::traits::Alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:98:47: required from here 98 | ResAlignment = traits >::Alignment | ^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix' 178 | class Matrix | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:46:50: required from 'class Eigen::QuaternionBase >' 46 | typedef typename Coefficients::CoeffReturnType CoeffReturnType; | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/Quaternion.h:273:7: required from 'class Eigen::Quaternion' 273 | class Quaternion : public QuaternionBase > | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Geometry/arch/Geometry_SIMD.h:102:3: required from here 102 | { | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/smart_ptr/shared_ptr.hpp:17, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/shared_ptr.hpp:17, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/date_time/time_clock.hpp:17, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/date_time/posix_time/posix_time_types.hpp:10, from D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:15, from D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/rstaninc.hpp:4: D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/smart_ptr/detail/shared_count.hpp:326:33: warning: 'template class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 326 | explicit shared_count( std::auto_ptr & r ): pi_( new sp_counted_impl_p( 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/4.5/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 class auto_ptr; | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/smart_ptr/shared_ptr.hpp:354:31: warning: 'template class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 354 | explicit shared_ptr( std::auto_ptr & 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 class auto_ptr; | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/smart_ptr/shared_ptr.hpp:365:22: warning: 'template class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 365 | shared_ptr( std::auto_ptr && 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 class auto_ptr; | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/smart_ptr/shared_ptr.hpp:423:34: warning: 'template class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 423 | shared_ptr & operator=( std::auto_ptr & 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 class auto_ptr; | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/smart_ptr/shared_ptr.hpp:430:34: warning: 'template class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 430 | shared_ptr & operator=( std::auto_ptr && 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 class auto_ptr; | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/smart_ptr/shared_ptr.hpp: In member function 'boost::shared_ptr& boost::shared_ptr::operator=(std::auto_ptr<_Up>&&)': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/smart_ptr/shared_ptr.hpp:432:38: warning: 'template class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 432 | this_type( static_cast< std::auto_ptr && >( 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 class auto_ptr; | ^~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/SparseCore:37, from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Sparse:26, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/Eigen.hpp:23: D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of 'class Eigen::SparseMatrixBase >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from 'class Eigen::SparseCompressedBase >' 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMatrix.h:96:7: required from 'class Eigen::SparseMatrix' 96 | class SparseMatrix | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h:61:25: required from here 61 | typedef Triplet T; | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits >' 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:19:52: required from 'struct Eigen::internal::traits > >' 19 | template struct traits > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59: required from 'struct Eigen::EigenBase > >' 42 | typedef typename internal::traits::StorageKind StorageKind; | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SolverBase.h:68:7: required from 'class Eigen::SolverBase > >' 68 | class SolverBase : public EigenBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:59:49: required from 'class Eigen::LDLT >' 59 | template class LDLT | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix' 178 | class Matrix | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:69:42: required from 'class Eigen::LDLT >' 69 | MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, | ^~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix' 178 | class Matrix | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:287:19: required from 'class Eigen::LDLT >' 287 | TmpMatrixType m_temporary; | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, 0> >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Array >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array > > >' 38 | >::type Scalar; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0> >, const Eigen::CwiseNullaryOp, Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, -1, 1, true>, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true>, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true>, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, true>, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, -1, 1, true>, -1, 1, false>, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, 1, true>, -1, 1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, 1, true>, -1, 1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock, -1, 1, true>, -1>' 56 | template class VectorBlock | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix' 178 | class Matrix | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from 'class Eigen::Array' 45 | class Array | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Array >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, 0> >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, const Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >' 38 | >::type Scalar; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Matrix >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from 'class Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>' 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:44: required from 'stan::math::ceil >(const Eigen::Matrix&):: [with auto:244 = Eigen::Matrix]' 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]' 47 | f(x)); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from 'auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]' 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/ceil.hpp:57:51: required from 'stan::math::ceil >(const Eigen::Matrix&):: [with auto:244 = Eigen::Matrix]' 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]' 47 | f(x)); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from 'auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]' 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary, void>::apply >(const Eigen::Matrix&):: >(const Eigen::Matrix&, const stan::math::ceil >(const Eigen::Matrix&)::&):: [with auto:6 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >]' 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, void>::apply >(const Eigen::Matrix&):: >(const Eigen::Matrix&, const stan::math::ceil >(const Eigen::Matrix&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::ceil >(const Eigen::Matrix&)::; T2 = Eigen::Matrix; stan::require_t::type> >* = 0; T = Eigen::Matrix]' 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/ceil.hpp:56:46: required from 'auto stan::math::ceil(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0; stan::require_not_var_matrix_t* = 0]' 56 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 57 | x, [](const auto& v) { return v.array().ceil(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::internal::member_minCoeff, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::internal::member_minCoeff, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::internal::member_minCoeff, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from 'class Eigen::PartialReduxExpr, Eigen::internal::member_minCoeff, 0>' 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, const Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >' 38 | >::type Scalar; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:27:19: required from here 27 | m_ += delta / num_samples_; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/welford_covar_estimator.hpp:27:19: required from here 27 | m_ += delta / num_samples_; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map, 0, Eigen::Stride<0, 0> >' 94 | template class Map | ^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/coupled_ode_system.hpp:77:63: required from here 77 | Eigen::Map(dz_dt.data(), dz_dt.size()) = f_y_t; | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor.hpp:13, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim.hpp:15, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/dump.hpp:7, from D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:43: D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function 'void stan::math::internal::combination(std::vector&, const int&, const int&, const int&)': D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function 'void stan::math::internal::combos(const int&, const double&, const int&, std::vector >&)': D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function 'void stan::math::internal::increment(std::vector&, const int&, const double&, const std::vector&, std::vector&)': D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:132:22: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector::size_type' {aka 'long long unsigned int'} [-Wsign-compare] 132 | while ((first_zero < index.size()) && index[first_zero]) { | ~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/hcubature.hpp:135:18: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector::size_type' {aka 'long long unsigned int'} [-Wsign-compare] 135 | if (first_zero == index.size()) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/functor/hcubature.hpp: In function 'void stan::math::internal::signcombos(const int&, const double&, const int&, std::vector >&)': D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map, 0, Eigen::Stride<0, 0> >' 94 | template class Map | ^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/ode_store_sensitivities.hpp:40:64: required from here 40 | coupled_state.size()); | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/mpl/aux_/na_assert.hpp:23, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/mpl/arg.hpp:25, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/mpl/placeholders.hpp:24, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/mpl/apply.hpp:24, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/serialization/array_optimization.hpp:18, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/serialization/array_wrapper.hpp:21, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/serialization/array.hpp:26, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/numeric/ublas/storage.hpp:22, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/numeric/ublas/vector.hpp:21, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/numeric/odeint/util/ublas_wrapper.hpp:23, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/numeric/odeint.hpp:25, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/ode_rk45.hpp:9, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/integrate_ode_rk45.hpp:6, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor.hpp:16: D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/mpl/assert.hpp: At global scope: D:/RCompile/CRANpkg/lib/4.5/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::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 196 | ); | ~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/mpl/assert.hpp:194:21: note: remove parentheses 194 | failed ************ (Pred::************ | ^~~~~~~~~~~~~~~~~~~ | - 195 | assert_arg( void (*)(Pred), typename assert_arg_pred::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 196 | ); | ~ | - D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/mpl/assert.hpp:199:21: warning: unnecessary parentheses in declaration of 'assert_not_arg' [-Wparentheses] 199 | failed ************ (boost::mpl::not_::************ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 200 | assert_not_arg( void (*)(Pred), typename assert_arg_pred_not::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 201 | ); | ~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/mpl/assert.hpp:199:21: note: remove parentheses 199 | failed ************ (boost::mpl::not_::************ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ | - 200 | assert_not_arg( void (*)(Pred), typename assert_arg_pred_not::type ) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 201 | ); | ~ | - In file included from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/fusion/functional/invocation/detail/that_ptr.hpp:13, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/fusion/functional/invocation/invoke.hpp:52, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/fusion/functional/adapter/fused.hpp:17, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/fusion/functional/generation/make_fused.hpp:13, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/fusion/include/make_fused.hpp:11, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/numeric/odeint/util/resize.hpp:30, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/numeric/odeint/util/state_wrapper.hpp:26, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/numeric/odeint/util/ublas_wrapper.hpp:33: D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/get_pointer.hpp:48:40: warning: 'template class std::auto_ptr' is deprecated: use 'std::unique_ptr' instead [-Wdeprecated-declarations] 48 | template T * get_pointer(std::auto_ptr 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 class auto_ptr; | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:39: required from 'stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]' 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]' 93 | return f(x); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_container_st* = 0]' 83 | return apply_vector_unary::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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, const Eigen::Array >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 38 | >::type Scalar; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from 'stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]' 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]' 93 | return f(x); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_container_st* = 0]' 83 | return apply_vector_unary::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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:42: required from 'stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]' 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]' 93 | return f(x); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_container_st* = 0]' 83 | return apply_vector_unary::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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:52: required from 'stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]' 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]' 93 | return f(x); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_container_st* = 0]' 83 | return apply_vector_unary::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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 5>, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 5>, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 5>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 5>, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 5>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 5>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Product, 5>, Eigen::Matrix, 0>, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_cholesky_rng.hpp:49:68: required from here 49 | return L_S.template triangularView() * B.transpose(); | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1>, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1>, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1>, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 1>, Eigen::Transpose >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 1>, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 1>, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_cholesky_rng.hpp:49:68: required from here 49 | return L_S.template triangularView() * B.transpose(); | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::TriangularView >, 2>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::TriangularView >, 2>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::TriangularView >, 2>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::TriangularView >, 2>, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::TriangularView >, 2>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::TriangularView >, 2>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::TriangularView >, 2>, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::TriangularView >, 2>, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::TriangularView >, 2>, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, Eigen::TriangularView >, 2>, 0>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:32: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, Eigen::Matrix, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, Eigen::Matrix >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, const Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >' 38 | >::type Scalar; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Transpose >, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 6>, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 6>, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 6>, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, 6>, Eigen::Matrix, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, 6>, Eigen::Matrix >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 6>, Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 6>, Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 6>, Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, 6>, Eigen::Matrix >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:51: recursively required by substitution of 'template const Eigen::internal::triangular_solve_retval >, 6>, Other> Eigen::TriangularViewImpl >, 6, Eigen::Dense>::solve(const Eigen::MatrixBase&) const [with int Side = ; Other = ]' 108 | * (D_ldlt.matrixU().solve( | ~~~~~~~~~~~~~~~~~~~~~~^ 109 | (Sigma_ldlt.matrixU().solve(X)).transpose())) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:108:51: required from here D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/ForwardDeclarations.h:32:48: required from 'struct Eigen::internal::accessors_level >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >' 32 | enum { has_direct_access = (traits::Flags & DirectAccessBit) ? 1 : 0, | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > >, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:32: required from here 110 | .transpose() | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > >, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:32: required from here 110 | .transpose() | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:110:43: required from here 110 | .transpose() | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:111:51: required from here 111 | * D_ldlt.transpositionsP()); | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Transpose >, 6>, Eigen::Transpose >, 6>, Eigen::Matrix > > > >, 2>, Eigen::Transpositions<-1, -1, int>, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/matrix_normal_prec_rng.hpp:111:52: required from here 111 | * D_ldlt.transpositionsP()); | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >]' 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: required from 'struct stan::math::apply_scalar_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, void>' 72 | apply_scalar_unary::apply(std::declval()))>; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/lgamma.hpp:120:50: required from 'auto stan::math::lgamma(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; stan::require_not_var_matrix_t* = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t* = 0]' 120 | return apply_scalar_unary::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/std_normal_ccdf_log.hpp:5, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob.hpp:328, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim.hpp:16: D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/std_normal_lccdf.hpp: In function 'stan::return_type_t stan::math::std_normal_lccdf(const T_y&)': D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/StanHeaders/include/src/stan/io/dump.hpp: In member function 'virtual std::vector > stan::io::dump::vals_c(const std::string&) const': D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/dump.hpp:694: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector::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/4.5/StanHeaders/include/src/stan/io/dump.hpp:707: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector::size_type' {aka 'long long unsigned int'} [-Wsign-compare] 707 | real_iter < val_i->second.first.size(); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, -1, -1, false>, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:102:0: required from here 102 | if (C_adj.size() > 0) { D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:111:0: required from here 111 | = D_adj.adjoint().template triangularView(); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 0>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, -1, -1, false>, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:116:0: required from here 116 | D_adj.diagonal() *= 0.5; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Ref.h:59:34: required from 'class Eigen::RefBase, 0, Eigen::OuterStride<> > >' 59 | template class RefBase | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Ref.h:281:76: required from 'class Eigen::Ref, 0, Eigen::OuterStride<> >' 281 | template class Ref | ^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:76:42: required from 'class Eigen::LLT, 0, Eigen::OuterStride<> >, 1>' 76 | MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime | ^~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map, 0, Eigen::Stride<0, 0> >' 94 | template class Map | ^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from 'class stan::math::arena_matrix, void>' 13 | class arena_matrix> D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/cholesky_decompose.hpp:144:0: required from here 144 | L_A.template triangularView().setZero(); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 28 | * arena_L_val.transpose(); D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() 28 | * arena_L_val.transpose(); D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of 'class Eigen::SparseMatrixBase >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from 'class Eigen::SparseCompressedBase >' 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: recursively required by substitution of 'template static std::true_type stan::is_base_pointer_convertible >::f(const Eigen::EigenBase*) [with OtherDerived = ]' 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible >' D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/is_eigen.hpp:21:71: required from 'struct stan::is_eigen >' 21 | : bool_constant::value> {}; | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:301:0: required by substitution of 'template class stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type> [with T = Eigen::SparseMatrix]' 301 | (is_eigen::value || is_kernel_expression_and_not_scalar::value) D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from here 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h: In instantiation of 'class Eigen::SparseMatrixBase, 0, Eigen::Stride<0, 0> > >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseCompressedBase.h:36:7: required from 'class Eigen::SparseCompressedBase, 0, Eigen::Stride<0, 0> > >' 36 | class SparseCompressedBase | ^~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:50:7: required from 'class Eigen::SparseMapBase, 0, Eigen::Stride<0, 0> >, 0>' 50 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:148:7: required from 'class Eigen::SparseMapBase, 0, Eigen::Stride<0, 0> >, 1>' 148 | class SparseMapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMap.h:222:7: required from 'class Eigen::Map, 0, Eigen::Stride<0, 0> >' 222 | class Map, Options, StrideType> | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:129:0: required from 'class stan::math::arena_matrix, void>' 129 | class arena_matrix> D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:814:0: required from 'class stan::math::vari_value, void>' 814 | using InnerIterator = typename arena_matrix::InnerIterator; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:419:0: required from 'const auto& stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::val() const [with T = Eigen::SparseMatrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 419 | inline const auto& val() const noexcept { return vi_->val(); } D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/csr_matrix_times_vector.hpp:120:0: required from here 120 | arena_t res = w_mat_arena.val() * value_of(b_arena); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/SparseCore/SparseMatrixBase.h:47:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 47 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, -1>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:97:21: required from 'class Eigen::Tridiagonalization >' 97 | >::type SubDiagonalReturnType; | ^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:111:62: required from 'class Eigen::SelfAdjointEigenSolver >' 111 | typedef typename TridiagonalizationType::SubDiagonalType SubDiagonalType; | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/eigendecompose_sym.hpp:40:0: required from here 40 | arena_t eigenvals = solver.eigenvalues(); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1>, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView, -1, 1> >::adj_Op, Eigen::Matrix, -1, 1> >' 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/grad.hpp:27:0: required from here 27 | g = x.adj(); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, 0> >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from 'stan::math::log, 0> >(const Eigen::Diagonal, 0>&):: [with auto:169 = Eigen::Diagonal, 0>]' 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]' 47 | f(x)); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]' 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from 'stan::math::log, 0> >(const Eigen::Diagonal, 0>&):: [with auto:169 = Eigen::Diagonal, 0>]' 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]' 47 | f(x)); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]' 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0> > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary, 0>, void>::apply, 0> >(const Eigen::Diagonal, 0>&):: >(const Eigen::Diagonal, 0>&, const stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::&):: [with auto:6 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >]' 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, 0>, void>::apply, 0> >(const Eigen::Diagonal, 0>&):: >(const Eigen::Diagonal, 0>&, const stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, 0> >(const Eigen::Diagonal, 0>&)::; T2 = Eigen::Diagonal, 0>; stan::require_t::type> >* = 0; T = Eigen::Diagonal, 0>]' 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::Diagonal, 0>; stan::require_container_st* = 0]' 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map, 0, Eigen::Stride<0, 0> >' 94 | template class Map | ^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from 'class stan::math::arena_matrix, void>' 13 | class arena_matrix> D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/log_softmax.hpp:81:0: required from here 81 | Eigen::Map(softmax_x_d_array, a_size) = softmax_x_d.array() / sum; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> >, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >' 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:67:0: required from here 67 | Eigen::Map(variRefB_, M_, N_).adj() += adjB; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Matrix >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_tri.hpp:85:0: required from here 85 | adjA = -adjB * Map(C_, M_, N_).transpose(); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Matrix >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_tri.hpp:85:0: required from here 85 | adjA = -adjB * Map(C_, M_, N_).transpose(); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Transpose > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Transpose >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map, 0, Eigen::Stride<0, 0> >' 94 | template class Map | ^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from 'class stan::math::arena_matrix, void>' 13 | class arena_matrix> D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, -1, 1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>' 56 | template class VectorBlock | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1, false> >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, -1, 1, false>, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, 1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, 1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock, -1>' 56 | template class VectorBlock | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Block, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false> >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1>' 56 | template class VectorBlock | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Block, -1, 1, false> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, false>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, false> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, 0, Eigen::Stride<0, 0> >, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/svd.hpp:56:0: required from here 56 | arena_Fp.diagonal().setZero(); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Transpose > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Transpose >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Transpose > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/svd.hpp:70:0: required from here 70 | .matrix() D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:61:0: required from here 61 | .matrix() D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Transpose > > > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/svd_V.hpp:61:0: required from here 61 | .matrix() D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:278:47: required from 'struct Eigen::internal::traits, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 278 | typedef typename DiagonalVectorType::Scalar Scalar; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/EigenBase.h:42:59: required from 'struct Eigen::EigenBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 42 | typedef typename internal::traits::StorageKind StorageKind; | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:18:7: required from 'class Eigen::DiagonalBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 18 | class DiagonalBase : public EigenBase | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DiagonalMatrix.h:293:7: required from 'class Eigen::DiagonalWrapper, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 293 | class DiagonalWrapper | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> >, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >' 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> >, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView*, -1, 1> > >::adj_Op, Eigen::Map*, -1, 1> > >' 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:80:0: required from here 80 | v1_map.adj() += di; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:111:0: required from here 111 | += 2 * adj_ * (v1_map.val() - Eigen::Map(v2_, length_)); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView*, -1, 1> > >::val_Op, Eigen::Map*, -1, 1> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/squared_distance.hpp:111:0: required from here 111 | += 2 * adj_ * (v1_map.val() - Eigen::Map(v2_, length_)); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >' 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0: required from here 27 | Eigen::Map(partials, size) = 2 * diff.array() / size_m1; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/variance.hpp:27:0: required from here 27 | Eigen::Map(partials, size) = 2 * diff.array() / size_m1; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl, -1, 1> >::val_Op, Eigen::Matrix, -1, 1>, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView, -1, 1> >::val_Op, Eigen::Matrix, -1, 1> >' 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/functor/jacobian.hpp:26:0: required from here 26 | fx = fx_var.val(); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of, -1, 1>&>(const Eigen::Matrix, -1, 1>&):: [with auto:11 = const Eigen::Matrix, -1, 1>]' 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::; Args = {const Eigen::Matrix, -1, 1, 0, -1, 1>&}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:73:21: required from 'auto stan::math::value_of(EigMat&&) [with EigMat = const Eigen::Matrix, -1, 1>&; stan::require_eigen_dense_base_t* = 0; stan::require_not_st_arithmetic* = 0]' 73 | return make_holder( | ~~~~~~~~~~~^ 74 | [](auto& a) { | ~~~~~~~~~~~~~ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 76 | }, | ~~ 77 | std::forward(M)); | ~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >' 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, Eigen::Matrix, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, Eigen::Matrix >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/functor/cvodes_integrator_adjoint.hpp:604:0: required from here 604 | f_y_t_vars.adj() = -Eigen::Map(NV_DATA_S(yB), N_); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/services/util/initialize.hpp:7, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/services/diagnose/diagnose.hpp:10, from D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:49: D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/random_var_context.hpp: In member function 'virtual std::vector > stan::io::random_var_context::vals_c(const std::string&) const': D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/random_var_context.hpp:111: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector::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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:351:0: required from here 351 | return (L_chol_ * eta) + mu_; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:351:0: required from here 351 | return (L_chol_ * eta) + mu_; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, const Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >' 38 | >::type Scalar; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 6>' 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >' 179 | typedef typename internal::find_best_packet::type PacketScalar; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 6>' 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 2>, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 2>, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 2>, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, 2>, Eigen::Matrix, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, 2>, Eigen::Matrix >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map, 0, Eigen::Stride<0, 0> >' 94 | template class Map | ^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/to_matrix.hpp:133:17: required from 'auto stan::math::to_matrix(const std::vector&, int, int) [with T = double]' 133 | return Eigen::Map>( | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 134 | &x[0], m, n); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:27:0: required from here 27 | covar = (n / (n + 5.0)) * covar D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: recursively required by substitution of 'template typename Eigen::ScalarBinaryOpTraits::Scalar, Eigen::internal::scalar_product_op::Scalar> >::ReturnType Eigen::MatrixBase >::dot(const Eigen::MatrixBase&) const [with OtherDerived = ]' 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from here D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:27:0: required from here 27 | var = (n / (n + 5.0)) * var D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseNullaryOp, Eigen::Matrix > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:7, from D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:68: D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/array_var_context.hpp: In member function 'virtual std::vector > stan::io::array_var_context::vals_c(const std::string&) const': D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/array_var_context.hpp:304: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector::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/4.5/StanHeaders/include/src/stan/io/array_var_context.hpp:317: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector::size_type' {aka 'long long unsigned int'} [-Wsign-compare] 317 | real_iter < val_i->second.first.size(); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, 1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, 1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:72:0: required from here 72 | Eigen::Map(&row[0], draws.cols()) = draws.row(i); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1>' 223 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map, 0, Eigen::Stride<0, 0> >' 94 | template class Map | ^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:13:0: required from 'class stan::math::arena_matrix, void>' 13 | class arena_matrix> D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/multiply.hpp:28:12: required from 'auto stan::math::multiply(const Mat&, Scal) [with Mat = Eigen::Matrix; Scal = int; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0; stan::require_all_not_complex_t::type>* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0; stan::require_all_not_complex_t::type>* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, 1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, 1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock, -1>' 56 | template class VectorBlock | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; stan::require_vector_t* = 0; stan::require_not_std_vector_t* = 0]' 187 | return v.segment(slice_start, slice_size); D:/RCompile/CRANpkg/lib/4.5/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 >; Idxs = {index_min_max}; stan::require_std_vector_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; stan::require_dense_dynamic_t* = 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/4.5/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 >; Idxs = {index_min_max, index_min_max}; stan::require_std_vector_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:158:0: required from 'stan::model::rvalue&>(const Eigen::Matrix&, const char*, const index_multi&):: [with auto:767 = const Eigen::Matrix]' 158 | return plain_type_t::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/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::model::rvalue&>(const Eigen::Matrix&, const char*, const index_multi&)::; Args = {const Eigen::Matrix&}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; stan::require_eigen_vector_t* = 0]' 156 | return stan::math::make_holder( 157 | [name, &idx](auto& v_ref) { 158 | return plain_type_t::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/4.5/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 >; Idxs = {index_multi}; stan::require_std_vector_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; L = int; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0; stan::return_type_t = double]' 102 | x.unaryExpr([lb, &lp](auto&& xx) { return lb_constrain(xx, lb, lp); })); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix; bool Jacobian = false; LB = int; LP = double; Sizes = {int}; T = double]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:14992:0: required from here 14991 | Theta_sd_free = in__.template read_constrain_lb< 14992 | Eigen::Matrix, jacobian__>(0, 14993 | lp__, Theta_sd_free_1dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >, const int&>(Eigen::Map, 0, Eigen::Stride<0, 0> >&&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/lb_constrain.hpp:83:26: required from 'auto stan::math::lb_constrain(T&&, L&&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; L = const int&; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0]' 83 | return eval(x.unaryExpr([lb](auto&& x) { return lb_constrain(x, lb); })); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:388:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix; bool Jacobian = false; LB = int; LP = double; Sizes = {int}; T = double]' 388 | return stan::math::lb_constrain(this->read(sizes...), lb); stanExports_stanmarg.h:14992:0: required from here 14991 | Theta_sd_free = in__.template read_constrain_lb< 14992 | Eigen::Matrix, jacobian__>(0, 14993 | lp__, Theta_sd_free_1dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, const int&, stan::return_type_t, 0, Eigen::Stride<0, 0> >, int, int>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_eigen_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_not_var_t::type>* = 0; stan::return_type_t = double]' 133 | return eval(x.unaryExpr( | ~~~~~~~~~~~^ 134 | [lb, ub, &lp](auto&& xx) { return lub_constrain(xx, lb, ub, lp); })); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix; bool Jacobian = false; LB = int; UB = int; LP = double; Sizes = {int}; T = double]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:14999:0: required from here 14998 | Theta_r_free = in__.template read_constrain_lub< 14999 | Eigen::Matrix, jacobian__>(-1, 15000 | 1, lp__, Theta_r_free_1dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> >, int, int>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const int&, const int&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_eigen_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_not_var_t::type>* = 0]' 122 | x.unaryExpr([ub, lb](auto&& xx) { return lub_constrain(xx, lb, ub); })); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:443:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix; bool Jacobian = false; LB = int; UB = int; LP = double; Sizes = {int}; T = double]' 443 | return stan::math::lub_constrain(this->read(sizes...), lb, ub); stanExports_stanmarg.h:14999:0: required from here 14998 | Theta_r_free = in__.template read_constrain_lub< 14999 | Eigen::Matrix, jacobian__>(-1, 15000 | 1, lp__, Theta_r_free_1dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Transpose > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Transpose >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >; Mat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Map, 0, Eigen::Stride<0, 0> >; Mat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, 1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, 1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock, -1>' 56 | template class VectorBlock | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; stan::require_vector_t* = 0; stan::require_not_std_vector_t* = 0]' 187 | return v.segment(slice_start, slice_size); D:/RCompile/CRANpkg/lib/4.5/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 >; Idxs = {index_min_max}; stan::require_std_vector_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Block, -1, 1, true>, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Block, -1, 1, true>, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Block, -1, 1, true>, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Block, -1, 1, true>, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Block, -1, 1, true>, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Block, -1, 1, true>, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from 'auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::VectorBlock, -1, 1, true>, -1>; stan::require_all_eigen_vt* = 0; stan::require_not_eigen_row_and_col_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:158:0: required from 'stan::model::rvalue&>(Eigen::Matrix&, const char*, const index_multi&):: [with auto:767 = Eigen::Matrix]' 158 | return plain_type_t::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/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::model::rvalue&>(Eigen::Matrix&, const char*, const index_multi&)::; Args = {Eigen::Matrix&}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; stan::require_eigen_vector_t* = 0]' 156 | return stan::math::make_holder( 157 | [name, &idx](auto& v_ref) { 158 | return plain_type_t::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/4.5/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 >; Idxs = {index_multi}; stan::require_std_vector_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; Mat2 = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const Eigen::Matrix, const Eigen::Matrix >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0; stan::require_all_not_complex_t::type>* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1, true> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, 1, true> >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar, -1, 1, true>&>(const Eigen::Block, -1, 1, true>&):: [with auto:13 = const Eigen::Block, -1, 1, true>]' 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar, -1, 1, true>&>(const Eigen::Block, -1, 1, true>&)::; Args = {const Eigen::Block, -1, 1, true>&}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, true>&; = void; stan::require_not_eigen_array_t* = 0]' 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:29: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Block, -1, 1, true>; T2 = int; stan::require_any_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:33: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Block, -1, 1, true>; T2 = int; stan::require_any_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, 1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:64: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Block, -1, 1, true>; T2 = int; stan::require_any_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; Idx = index_omni; stan::require_dense_dynamic_t* = 0]' 661 | return rvalue(x.middleCols(col_start, col_idx.max_ - col_start), name, D:/RCompile/CRANpkg/lib/4.5/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 >; Idxs = {index_omni, index_min_max}; stan::require_std_vector_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, -1, true> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, -1, true> >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar, -1, -1, true>&>(const Eigen::Block, -1, -1, true>&):: [with auto:13 = const Eigen::Block, -1, -1, true>]' 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar, -1, -1, true>&>(const Eigen::Block, -1, -1, true>&)::; Args = {const Eigen::Block, -1, -1, true>&}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, true>&; = void; stan::require_not_eigen_array_t* = 0]' 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:29: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Block, -1, -1, true>; T2 = int; stan::require_any_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:33: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Block, -1, -1, true>; T2 = int; stan::require_any_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:64: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Block, -1, -1, true>; T2 = int; stan::require_any_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/transpose.hpp:18:21: required from 'auto stan::math::transpose(const T&) [with T = Eigen::Matrix; stan::require_matrix_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from 'auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Transpose >; stan::require_all_eigen_vt* = 0; stan::require_not_eigen_row_and_col_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::Product, Eigen::Transpose >, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::Product, Eigen::Transpose >, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::Product, Eigen::Transpose >, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::Product, Eigen::Transpose >, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, const Eigen::Product, Eigen::Transpose >, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::ArrayWrapper, -1, -1, true> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Mat2 = Eigen::Product, Eigen::Transpose >, 0>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/transpose.hpp:18:21: required from 'auto stan::math::transpose(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; stan::require_matrix_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:33: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Matrix; T2 = int; stan::require_any_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/divide.hpp:47:64: required from 'auto stan::math::divide(const T1&, const T2&) [with T1 = Eigen::Matrix; T2 = int; stan::require_any_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, 0, Eigen::Stride<0, 0> >, -1, 1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>' 56 | template class VectorBlock | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >&; stan::require_vector_t* = 0; stan::require_not_std_vector_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::VectorBlock, 0, Eigen::Stride<0, 0> >, -1>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Block, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Block, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Block, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Block, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Block, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::VectorBlock, -1>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:35: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits >' 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Array.h:17:8: required from 'struct Eigen::internal::traits >' 17 | struct traits > : traits > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from 'class Eigen::Array' 45 | class Array | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 28 | ArrayAT a_array = as_array_or_scalar(a); | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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* = 0]' 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from 'class Eigen::Array' 45 | class Array | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 28 | ArrayAT a_array = as_array_or_scalar(a); | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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* = 0]' 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Map.h:94:79: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar&>(const std::vector&)::; Args = {const std::vector >&}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; stan::require_std_vector_t* = 0; stan::require_not_std_vector_t::type>* = 0]' 72 | return make_holder([](auto& x) { return T_map(x.data(), x.size()); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 73 | std::forward(v)); | ~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 28 | ArrayAT a_array = as_array_or_scalar(a); | ~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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* = 0]' 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Array >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > > >' 38 | >::type Scalar; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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* = 0]' 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Select.h:52:7: required from 'class Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >' 52 | class Select : public internal::dense_xpr_base< Select >::type, | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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* = 0]' 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/fabs.hpp:67:50: required from 'stan::math::fabs, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >(const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >&):: [with auto:9 = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >]' 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::fabs, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >(const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >&)::; T2 = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >; stan::require_t::type> >* = 0; T = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >]' 53 | return make_holder([](const auto& a) { return a.array().derived(); }, f(x)); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/fabs.hpp:66:46: required from 'auto stan::math::fabs(const Container&) [with Container = Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array >; stan::require_container_st* = 0]' 66 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 67 | x, [](const auto& v) { return v.array().abs(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 47 | const auto& abs_apk = math::fabs((apk == 0).select(1.0, apk)); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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* = 0]' 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from 'stan::math::log, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >(const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >&):: [with auto:169 = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >]' 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:53:76: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > > >(const Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >&)::; T2 = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >; stan::require_t::type> >* = 0; T = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >]' 53 | return make_holder([](const auto& a) { return a.array().derived(); }, f(x)); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::CwiseUnaryOp, const Eigen::Select, const Eigen::Array, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::CwiseNullaryOp, Eigen::Array >, Eigen::Array > >; stan::require_container_st* = 0]' 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 49 | T_return p = sum(log(abs_apk)) - sum(log(abs_bpk)); | ~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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* = 0]' 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:75: required from 'stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]' 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:32: required from 'stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]' 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]' 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:72:38: required from 'struct stan::math::apply_scalar_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>' 72 | apply_scalar_unary::apply(std::declval()))>; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/lgamma.hpp:120:50: required from 'auto stan::math::lgamma(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseNullaryOp, Eigen::Array > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_not_var_matrix_t* = 0; stan::require_not_nonscalar_prim_or_rev_kernel_expression_t* = 0]' 120 | return apply_scalar_unary::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/lmgamma.hpp:58:29: required from 'stan::return_type_t stan::math::lmgamma(int, T) [with T = double; stan::require_arithmetic_t* = 0; stan::return_type_t = double]' 58 | return result + sum(lgamma(x + (1 - Eigen::ArrayXd::LinSpaced(k, 1, k)) / 2)); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Matrix >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Matrix; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/variance.hpp:28:0: required from here 28 | double variance = diff.squaredNorm() / size_m1; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Array.h:45:7: required from 'class Eigen::Array' 45 | class Array | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67: required from 'Derived& Eigen::ArrayBase::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper >; Scalar = double]' 27 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:280:0: required from here 280 | L_chol_.array() += scalar; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Array >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:27:67: required from 'Derived& Eigen::ArrayBase::operator+=(const Scalar&) [with Derived = Eigen::ArrayWrapper >; Scalar = double]' 27 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::add_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/variational/families/normal_fullrank.hpp:280:0: required from here 280 | L_chol_.array() += scalar; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/array_var_context.hpp: In instantiation of 'std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long long unsigned int]': D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/array_var_context.hpp:97:0: required from here 97 | std::vector dim_vec = validate_dims(names, values.size(), dims); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/array_var_context.hpp:74: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector >::size_type' {aka 'long long unsigned int'} [-Wsign-compare] 74 | for (int i = 0; i < dims.size(); i++) { D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/array_var_context.hpp: In instantiation of 'std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [with T = long long int]': D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/array_var_context.hpp:118:0: required from here 118 | std::vector dim_vec = validate_dims(names, values.size(), dims); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/array_var_context.hpp:74: warning: comparison of integer expressions of different signedness: 'int' and 'std::vector >::size_type' {aka 'long long unsigned int'} [-Wsign-compare] 74 | for (int i = 0; i < dims.size(); i++) { D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&)::::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of_rec.hpp:110:27: required from 'stan::math::value_of_rec, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&):: [with auto:1 = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 110 | return m.unaryExpr([](auto x) { return value_of_rec(x); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of_rec, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&)::; Args = {Eigen::Map, 0, Eigen::Stride<0, 0> >}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; = void; = void]' 108 | return make_holder( | ~~~~~~~~~~~^ 109 | [](auto& m) { | ~~~~~~~~~~~~~ 110 | return m.unaryExpr([](auto x) { return value_of_rec(x); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | }, | ~~ 112 | std::forward(M)); | ~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_low = int; stan::require_vector_t* = 0; stan::require_not_std_vector_vt* = 0; stan::require_stan_scalar_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/fun/tanh.hpp:58:46: required from 'auto stan::math::tanh(const Container&) [with Container = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_container_st* = 0]' 58 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 59 | x, [](const auto& v) { return v.array().tanh(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; T_lp = double]' 47 | plain_type_t tanh_x = tanh(x); | ~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:41: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/fun/tanh.hpp:58:46: required from 'auto stan::math::tanh(const Container&) [with Container = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_container_st* = 0]' 58 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 59 | x, [](const auto& v) { return v.array().tanh(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; T_lp = double]' 47 | plain_type_t tanh_x = tanh(x); | ~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:41: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary, 0, Eigen::Stride<0, 0> >, void>::apply, 0, Eigen::Stride<0, 0> > >(const Eigen::Map, 0, Eigen::Stride<0, 0> >&):: >(const Eigen::Map, 0, Eigen::Stride<0, 0> >&, const stan::math::tanh, 0, Eigen::Stride<0, 0> > >(const Eigen::Map, 0, Eigen::Stride<0, 0> >&)::&):: [with auto:6 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >]' 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/fun/tanh.hpp:58:46: required from 'auto stan::math::tanh(const Container&) [with Container = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_container_st* = 0]' 58 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 59 | x, [](const auto& v) { return v.array().tanh(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; T_lp = double]' 47 | plain_type_t tanh_x = tanh(x); | ~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:41: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary, void>::apply >(const Eigen::Matrix&):: >(const Eigen::Matrix&, const stan::math::square >(const Eigen::Matrix&)::&):: [with auto:6 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >]' 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/fun/square.hpp:69:46: required from 'auto stan::math::square(const Container&) [with Container = Eigen::Matrix; stan::require_container_st* = 0]' 69 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 70 | x, [](const auto& v) { return v.array().square(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; T_lp = double]' 48 | lp += sum(log1m(square(tanh_x))); | ~~~~~~^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:41: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >&)::, const Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >&)::, const Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >&)::, const Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >&)::, const Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, void>::apply(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >&)::, const Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/fun/log1m.hpp:74:49: required from 'auto stan::math::log1m(const T&) [with T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper > > >; stan::require_not_var_matrix_t* = 0; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0]' 74 | return apply_scalar_unary::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; T_lp = double]' 48 | lp += sum(log1m(square(tanh_x))); | ~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:41: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:35: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Transpose > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Transpose > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Transpose > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::Transpose > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::Transpose > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, Eigen::Transpose > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::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; VecI = std::vector; stan::require_vector_t* = 0; stan::require_vector_like_vt* = 0; std::ostream = std::basic_ostream]': 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::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; VecI = std::vector; stan::require_vector_t* = 0; stan::require_vector_like_vt* = 0; std::ostream = std::basic_ostream]': 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::min(); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp: In instantiation of 'SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]': stanExports_stanmarg.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits >' 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix' 178 | class Matrix | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:181:31: required from 'stan::return_type_t 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; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]' 181 | Eigen::Matrix a_args(2); | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/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]' 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >* = 0]' 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix' 178 | class Matrix | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:181:31: required from 'stan::return_type_t 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; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]' 181 | Eigen::Matrix a_args(2); | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/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]' 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >* = 0]' 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix' 178 | class Matrix | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:182:31: required from 'stan::return_type_t 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; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]' 182 | Eigen::Matrix b_args(1); | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/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]' 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >* = 0]' 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Array >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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]' 117 | inner_diff = g_current.array().abs().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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]' 204 | grad_tuple_ab = grad_2F1_impl_ab( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 205 | a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >* = 0]' 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/plugins/CommonCwiseUnaryOps.h:62:1: required by substitution of 'template typename Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::CastXpr::Type Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >::cast() const [with NewType = double]' 62 | cast() const | ^~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]' 102 | result << A.template cast(), B; | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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* = 0]' 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/err/check_not_nan.hpp:5, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/err/check_2F1_converges.hpp:5, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/err.hpp:4, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim.hpp:12: D:/RCompile/CRANpkg/lib/4.5/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 >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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]' 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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 >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)(((!(Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit)) && (! T::IsVectorAtCompileTime)) && (!(Eigen::internal::traits<_Rhs>::Flags & Eigen::RowMajorBit))))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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]' 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/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 >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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]' 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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 >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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]' 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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 >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Matrix > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Matrix > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28: required from 'bool Eigen::DenseBase::hasNaN() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >]' 142 | return !((derived().array()==derived().array()).all()); | ~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:40: required from 'bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]' 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/covar_adaptation.hpp:31:0: required from here 31 | if (!covar.allFinite()) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Matrix, const Eigen::Matrix > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, const Eigen::Matrix, const Eigen::Matrix > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:142:28: required from 'bool Eigen::DenseBase::hasNaN() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >]' 142 | return !((derived().array()==derived().array()).all()); | ~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/BooleanRedux.h:156:40: required from 'bool Eigen::DenseBase::allFinite() const [with Derived = Eigen::Matrix]' 156 | return !((derived()-derived()).hasNaN()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/var_adaptation.hpp:30:0: required from here 30 | if (!var.allFinite()) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta.hpp:70, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/err/invalid_argument.hpp:4, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/core/init_threadpool_tbb.hpp:4, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/core.hpp:4, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim.hpp:10: D:/RCompile/CRANpkg/lib/4.5/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* = 0; Idxs = {}]': D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/array_var_context.hpp:79:0: required from 'std::vector stan::io::array_var_context::validate_dims(const std::vector >&, T, const std::vector >&) [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/4.5/StanHeaders/include/src/stan/io/array_var_context.hpp:118:0: required from here 118 | std::vector dim_vec = validate_dims(names, values.size(), dims); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:79:21: required from 'auto stan::math::subtract(const Mat&, Scal) [with Mat = Eigen::Matrix; Scal = int; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0]' 79 | return (m.array() - c).matrix(); | ~~~~~~~~~~~^~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 37 | return eval(log(subtract(std::forward(y_ref), | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from 'void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:79:32: required from 'auto stan::math::subtract(const Mat&, Scal) [with Mat = Eigen::Matrix; Scal = int; stan::require_eigen_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_all_not_st_var* = 0]' 79 | return (m.array() - c).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 37 | return eval(log(subtract(std::forward(y_ref), | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from 'void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from 'stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: [with auto:169 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]' 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]' 47 | f(x)); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]' 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 37 | return eval(log(subtract(std::forward(y_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from 'void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from 'stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: [with auto:169 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]' 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]' 47 | f(x)); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]' 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 37 | return eval(log(subtract(std::forward(y_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from 'void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&, const stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::&):: [with auto:6 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >]' 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, void>::apply, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):: >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&, const stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:23: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >]' 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 47 | f(x)); | ~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]' 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 37 | return eval(log(subtract(std::forward(y_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | std::forward(lb_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:253:0: required from 'void stan::io::serializer::write_free_lb(const L&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 62 | return (c - m.array()).matrix(); | ~~~^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/ub_free.hpp:43:29: required from 'auto stan::math::ub_free(T&&, U&&) [with T = Eigen::Matrix; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 43 | return eval(log(subtract(std::forward(ub_ref), | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 44 | std::forward(y_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_all_stan_scalar_t* = 0]' 54 | return ub_free(identity_free(y, lb), ub); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 62 | return (c - m.array()).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/ub_free.hpp:43:29: required from 'auto stan::math::ub_free(T&&, U&&) [with T = Eigen::Matrix; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 43 | return eval(log(subtract(std::forward(ub_ref), | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 44 | std::forward(y_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_all_stan_scalar_t* = 0]' 54 | return ub_free(identity_free(y, lb), ub); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:66:44: required from 'stan::math::log, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >&):: [with auto:169 = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >]' 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:47:25: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::apply(const T&, const F&) [with F = stan::math::log, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >&)::; T2 = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >; stan::require_t::type> >* = 0; T = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >]' 47 | f(x)); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >; stan::require_container_st* = 0]' 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/ub_free.hpp:43:20: required from 'auto stan::math::ub_free(T&&, U&&) [with T = Eigen::Matrix; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 43 | return eval(log(subtract(std::forward(ub_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 44 | std::forward(y_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_all_stan_scalar_t* = 0]' 54 | return ub_free(identity_free(y, lb), ub); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >; stan::require_container_st* = 0]' 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/ub_free.hpp:43:20: required from 'auto stan::math::ub_free(T&&, U&&) [with T = Eigen::Matrix; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 43 | return eval(log(subtract(std::forward(ub_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 44 | std::forward(y_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_all_stan_scalar_t* = 0]' 54 | return ub_free(identity_free(y, lb), ub); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >, void>::apply, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >&):: >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >&, const stan::math::log, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >(const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >&)::&):: [with auto:6 = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >]' 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:65:46: required from 'auto stan::math::log(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >; stan::require_container_st* = 0]' 65 | return apply_vector_unary::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/ub_free.hpp:43:20: required from 'auto stan::math::ub_free(T&&, U&&) [with T = Eigen::Matrix; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 43 | return eval(log(subtract(std::forward(ub_ref), | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 44 | std::forward(y_ref)))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_all_stan_scalar_t* = 0]' 54 | return ub_free(identity_free(y, lb), ub); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; T2 = double; stan::require_any_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_all_stan_scalar_t* = 0]' 59 | return eval(logit(divide(subtract(std::forward(y_ref), lb), | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 60 | subtract(ub, lb)))); | ~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; T2 = double; stan::require_any_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 47 | return (as_array_or_scalar(m) / as_array_or_scalar(c)).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_all_stan_scalar_t* = 0]' 59 | return eval(logit(divide(subtract(std::forward(y_ref), lb), | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 60 | subtract(ub, lb)))); | ~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/logit.hpp:113:51: required from 'stan::math::logit, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):::: [with auto:341 = Eigen::Matrix]' 113 | [](const auto& v) { return (v.array() / (1 - v.array())).log(); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::logit, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; Args = {Eigen::Matrix}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/logit.hpp:109:21: required from 'auto stan::math::logit(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]' 109 | return make_holder( | ~~~~~~~~~~~^ 110 | [](const auto& v_ref) { | ~~~~~~~~~~~~~~~~~~~~~~~ 111 | return apply_vector_unary>::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | v_ref, | ~~~~~~ 113 | [](const auto& v) { return (v.array() / (1 - v.array())).log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 114 | }, | ~~ 115 | to_ref(x)); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_all_stan_scalar_t* = 0]' 59 | return eval(logit(divide(subtract(std::forward(y_ref), lb), | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 60 | subtract(ub, lb)))); | ~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/logit.hpp:113:73: required from 'stan::math::logit, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):::: [with auto:341 = Eigen::Matrix]' 113 | [](const auto& v) { return (v.array() / (1 - v.array())).log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::logit, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; Args = {Eigen::Matrix}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/logit.hpp:109:21: required from 'auto stan::math::logit(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]' 109 | return make_holder( | ~~~~~~~~~~~^ 110 | [](const auto& v_ref) { | ~~~~~~~~~~~~~~~~~~~~~~~ 111 | return apply_vector_unary>::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | v_ref, | ~~~~~~ 113 | [](const auto& v) { return (v.array() / (1 - v.array())).log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 114 | }, | ~~ 115 | to_ref(x)); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_all_stan_scalar_t* = 0]' 59 | return eval(logit(divide(subtract(std::forward(y_ref), lb), | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 60 | subtract(ub, lb)))); | ~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:46:59: required from 'stan::math::apply_vector_unary, void>::apply, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):::: >(const Eigen::Matrix&, const stan::math::logit, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::::&):: [with auto:6 = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >]' 46 | return make_holder([](const auto& a) { return a.matrix().derived(); }, | ~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::apply_vector_unary, void>::apply, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&):::: >(const Eigen::Matrix&, const stan::math::logit, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::::&)::; Args = {Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::logit, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; Args = {Eigen::Matrix}; stan::require_plain_type_t()((declval)()...))>* = ]' D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/logit.hpp:109:21: required from 'auto stan::math::logit(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]' 109 | return make_holder( | ~~~~~~~~~~~^ 110 | [](const auto& v_ref) { | ~~~~~~~~~~~~~~~~~~~~~~~ 111 | return apply_vector_unary>::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | v_ref, | ~~~~~~ 113 | [](const auto& v) { return (v.array() / (1 - v.array())).log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 114 | }, | ~~ 115 | to_ref(x)); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_all_stan_scalar_t* = 0]' 59 | return eval(logit(divide(subtract(std::forward(y_ref), lb), | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 60 | subtract(ub, lb)))); | ~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:115:7: required from 'class stan::math::Holder, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >, Eigen::Matrix >' 115 | class Holder | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const std::tuple&) [with T = Eigen::MatrixWrapper, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >; long long unsigned int ...Is = {0}; Args = {Eigen::Matrix}; std::index_sequence = std::integer_sequence]' 312 | return holder(std::forward(expr), std::get(ptrs)...); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:330:43: required from 'auto stan::math::internal::make_holder_impl(const F&, std::index_sequence, Args&& ...) [with F = stan::math::logit, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; long long unsigned int ...Is = {0}; Args = {Eigen::Matrix}; std::index_sequence = std::integer_sequence]' 330 | return make_holder_impl_construct_object( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 331 | func(*std::get(res)...), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 332 | std::make_index_sequence::value>(), ptrs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:353:36: required from 'auto stan::math::make_holder(const F&, Args&& ...) [with F = logit, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >(const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >&)::; Args = {Eigen::Matrix}; stan::require_not_plain_type_t()((declval)()...))>* = 0]' 353 | return internal::make_holder_impl(func, | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ 354 | std::make_index_sequence(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 355 | std::forward(args)...); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/logit.hpp:109:21: required from 'auto stan::math::logit(const Container&) [with Container = Eigen::MatrixWrapper, const Eigen::ArrayWrapper, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; stan::require_container_st* = 0]' 109 | return make_holder( | ~~~~~~~~~~~^ 110 | [](const auto& v_ref) { | ~~~~~~~~~~~~~~~~~~~~~~~ 111 | return apply_vector_unary>::apply( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 112 | v_ref, | ~~~~~~ 113 | [](const auto& v) { return (v.array() / (1 - v.array())).log(); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 114 | }, | ~~ 115 | to_ref(x)); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&; L = const int&; U = const int&; stan::require_not_std_vector_t* = 0; stan::require_all_stan_scalar_t* = 0]' 59 | return eval(logit(divide(subtract(std::forward(y_ref), lb), | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 60 | subtract(ub, lb)))); | ~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:281:0: required from 'void stan::io::serializer::write_free_lub(const L&, const U&, const S&) [with S = Eigen::Matrix; 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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]': D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1253:0: required from 'SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1253 | ret = stan::services::standalone_generate(model_, draws, 1254 | Rcpp::as(seed), interrupt, logger, *sample_writer_ptr); stanExports_stanmarg.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/services/sample/standalone_gqs.hpp:55: warning: comparison of integer expressions of different signedness: 'std::vector >::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/4.5/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/4.5/BH/include/boost/concept/assert.hpp:35, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept_check.hpp:20, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:19, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/size_type.hpp:20, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/size.hpp:21, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/functions.hpp:20, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range.hpp:18, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/numeric/odeint/util/resize.hpp:24: D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FinderConcept >, __gnu_cxx::__normal_iterator > >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:81:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/BH/include/boost/algorithm/string/iter_find.hpp:26, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/split.hpp:16, from D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string.hpp:23, from D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:4, from D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:46: D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/concept.hpp:40: note: in a call to non-static member function 'void boost::algorithm::FinderConcept::constraints() [with FinderT = boost::algorithm::detail::token_finderF >; IteratorT = __gnu_cxx::__normal_iterator >]' 40 | void constraints() D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FinderConcept, __gnu_cxx::__normal_iterator > >]': D:/RCompile/CRANpkg/lib/4.5/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; FinderT = detail::first_finderF; FormatterT = detail::const_formatF >]' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; 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/4.5/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:133:0: required from here 133 | boost::replace_first(value, " (Default)", ""); D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/algorithm/string/concept.hpp:40: note: in a call to non-static member function 'void boost::algorithm::FinderConcept::constraints() [with FinderT = boost::algorithm::detail::first_finderF; IteratorT = __gnu_cxx::__normal_iterator >]' 40 | void constraints() D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::constraint::failed() [with Model = boost::algorithm::FormatterConcept >, boost::algorithm::detail::first_finderF, __gnu_cxx::__normal_iterator > >]': D:/RCompile/CRANpkg/lib/4.5/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; FinderT = detail::first_finderF; FormatterT = detail::const_formatF >]' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; 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/4.5/StanHeaders/include/src/stan/io/stan_csv_reader.hpp:133:0: required from here 133 | boost::replace_first(value, " (Default)", ""); D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/algorithm/string/concept.hpp:65: note: in a call to non-static member function 'void boost::algorithm::FormatterConcept::constraints() [with FormatterT = boost::algorithm::detail::const_formatF >; FinderT = boost::algorithm::detail::first_finderF; IteratorT = __gnu_cxx::__normal_iterator >]' 65 | void constraints() D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<1> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<1> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::InnerStride<1> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::InnerStride<1> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::InnerStride<1> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Ref.h:59:34: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:112:44: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_L(const T&, size_t, stan::value_type_t&) [with T = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int; stan::value_type_t = double]' 112 | const Eigen::Ref>& CPCs_ref = CPCs; | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:55: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t&) [with T_CPCs = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int; stan::value_type_t = double]' 61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Array >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:62:47: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_L(const T&, size_t) [with T = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int]' 62 | acc.tail(pull) = T_scalar(1.0) - temp.square(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:32:55: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t) [with T_CPCs = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int]' 32 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K)); | ~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:45:26: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int]' 45 | return read_corr_matrix(corr_constrain(x), k); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:949:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 949 | return corr_matrix_constrain( 950 | this->read>((k * (k - 1)) / 2), 951 | k); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:62:34: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_L(const T&, size_t) [with T = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int]' 62 | acc.tail(pull) = T_scalar(1.0) - temp.square(); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:32:55: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t) [with T_CPCs = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int]' 32 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K)); | ~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:45:26: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int]' 45 | return read_corr_matrix(corr_constrain(x), k); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:949:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 949 | return corr_matrix_constrain( 950 | this->read>((k * (k - 1)) / 2), 951 | k); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, false> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, false> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, false> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, false> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, false> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:68:32: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_L(const T&, size_t) [with T = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int]' 68 | L.col(i).tail(pull) = temp * acc.tail(pull).sqrt(); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:32:55: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t) [with T_CPCs = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int]' 32 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K)); | ~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:45:26: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int]' 45 | return read_corr_matrix(corr_constrain(x), k); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:949:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 949 | return corr_matrix_constrain( 950 | this->read>((k * (k - 1)) / 2), 951 | k); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_sum_exp.hpp:92:58: required from 'stan::math::log_sum_exp >(const Eigen::Matrix&):: [with auto:304 = Eigen::Matrix]' 92 | return max + std::log((v_ref.array() - max).exp().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::log_sum_exp >(const Eigen::Matrix&)::; T = Eigen::Matrix]' 93 | return f(x); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_container_st* = 0]' 83 | return apply_vector_unary::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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Core:330: D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'class Eigen::internal::gebp_traits': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:72:102: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [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 ResMapper; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]' 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]' 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'class Eigen::internal::gebp_traits': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1080:42: required from 'struct Eigen::internal::gebp_kernel, 4, 4, false, false>' 1080 | typedef typename HalfTraits::LhsPacket LhsPacketHalf; | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:92:109: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [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 gebp; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]' 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]' 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'class Eigen::internal::gebp_traits': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:1085:45: required from 'struct Eigen::internal::gebp_kernel, 4, 4, false, false>' 1085 | typedef typename QuarterTraits::LhsPacket LhsPacketQuarter; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:92:109: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [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 gebp; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]' 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]' 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:425:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 425 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:426:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 426 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:427:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 427 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:49: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 432 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && unpacket_traits<_RhsPacket>::vectorizable, | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:432:94: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 433 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:433:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 434 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:434:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 435 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:435:65: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 460 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:460:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 461 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:461:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 462 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:462:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 465 | typedef QuadPacket RhsPacketx4; | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:465:33: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CommaInitializer.h:159:10: required from 'Eigen::CommaInitializer Eigen::DenseBase::operator<<(const Eigen::DenseBase&) [with OtherDerived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix]' 159 | return CommaInitializer(*static_cast(this), other); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10: required from 'Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]' 102 | result << A.template cast(), B; | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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* = 0]' 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Matrix; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Matrix; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:478:32: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::mean() const [with Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]' 478 | return Scalar(derived().redux(Eigen::internal::scalar_sum_op())) / Scalar(this->size()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, -1>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:451:40: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 451 | subdiag = mat.template diagonal<-1>().real(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, 1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:91: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; 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/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false>, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false>, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, false>, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: required from 'class Eigen::VectorBlock, 1, -1, false>, -1>' 56 | template class VectorBlock | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:101: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; 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/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<1> >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<1> >, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::InnerStride<1> >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::InnerStride<1> >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::InnerStride<1> >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::InnerStride<1> >, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:126:21: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_L(const T&, size_t, stan::value_type_t&) [with T = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int; stan::value_type_t = double]' 126 | return read_corr_L(CPCs_ref, K); | ~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:55: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t&) [with T_CPCs = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int; stan::value_type_t = double]' 61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_eigen_matrix_dynamic_t* = 0; stan::require_not_st_autodiff* = 0; matrix_d = Eigen::Matrix]' 35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:43: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t&) [with T_CPCs = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int; stan::value_type_t = double]' 61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Matrix >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:191:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 191 | _pk.noalias() = -_gk; D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12962 | Theta_sd_free = in__.template read_constrain_lb< 12963 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12962 | Theta_sd_free = in__.template read_constrain_lb< 12963 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]' 192 | auto exp_x = to_arena(arena_x.val().array().exp()); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12962 | Theta_sd_free = in__.template read_constrain_lb< 12963 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]' 193 | arena_t ret = exp_x + lb_val; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12962 | Theta_sd_free = in__.template read_constrain_lb< 12963 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12962 | Theta_sd_free = in__.template read_constrain_lb< 12963 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12962 | Theta_sd_free = in__.template read_constrain_lb< 12963 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]' 197 | arena_x.adj().array() += ret.adj().array() * exp_x + lp.adj(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12962 | Theta_sd_free = in__.template read_constrain_lb< 12963 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]' 197 | arena_x.adj().array() += ret.adj().array() * exp_x + lp.adj(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12962 | Theta_sd_free = in__.template read_constrain_lb< 12963 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&):: [with auto:11 = const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >]' 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12962 | Theta_sd_free = in__.template read_constrain_lb< 12963 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]' 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12962 | Theta_sd_free = in__.template read_constrain_lb< 12963 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]' 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12962 | Theta_sd_free = in__.template read_constrain_lb< 12963 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]' 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:386:0: required from 'auto stan::io::deserializer::read_constrain_lb(const LB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 386 | return stan::math::lb_constrain(this->read(sizes...), lb, lp); stanExports_stanmarg.h:12963:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12962 | Theta_sd_free = in__.template read_constrain_lb< 12963 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Matrix, -1, 1>; L = int; stan::require_matrix_t* = 0; stan::require_stan_scalar_t* = 0; stan::require_any_st_var* = 0; stan::return_type_t = var_value]' 213 | arena_t ret = value_of(x_ref).array().exp() + lb_val; D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 209 | return ret_type(lb_constrain(identity_constrain(x, ub), lb, lp)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of, -1, 1> >&>(arena_matrix, -1, 1> >&):: [with auto:11 = stan::math::arena_matrix, -1, 1> >]' 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 215 | auto neg_abs_x = to_arena(-(value_of(arena_x).array()).abs()); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 215 | auto neg_abs_x = to_arena(-(value_of(arena_x).array()).abs()); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 215 | auto neg_abs_x = to_arena(-(value_of(arena_x).array()).abs()); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1p_exp_fun; T = stan::math::arena_matrix, void>]' 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 217 | lp += (log(diff) + (neg_abs_x - (2.0 * log1p_exp(neg_abs_x)))).sum(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 217 | lp += (log(diff) + (neg_abs_x - (2.0 * log1p_exp(neg_abs_x)))).sum(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, void>, void>::apply(const stan::math::arena_matrix, void>&)::, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 217 | lp += (log(diff) + (neg_abs_x - (2.0 * log1p_exp(neg_abs_x)))).sum(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::ArrayWrapper, -1, 1> >&>(arena_matrix, -1, 1> >&)::::, const Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >]' 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 219 | arena_t ret = diff * inv_logit_x + lb_val; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 219 | arena_t ret = diff * inv_logit_x + lb_val; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 224 | += ret.adj().array() * diff * inv_logit_x * (1.0 - inv_logit_x) D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 224 | += ret.adj().array() * diff * inv_logit_x * (1.0 - inv_logit_x) D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 224 | += ret.adj().array() * diff * inv_logit_x * (1.0 - inv_logit_x) D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 224 | += ret.adj().array() * diff * inv_logit_x * (1.0 - inv_logit_x) D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 225 | + lp.adj() * (1.0 - 2.0 * inv_logit_x); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 225 | + lp.adj() * (1.0 - 2.0 * inv_logit_x); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 225 | + lp.adj() * (1.0 - 2.0 * inv_logit_x); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >; L = int; U = int; stan::require_matrix_t* = 0; stan::require_all_stan_scalar_t* = 0; stan::require_var_t::type>* = 0; stan::return_type_t = var_value]' 231 | += (ret.adj().array() * (1.0 - inv_logit_x)).sum() D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:441:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 441 | return stan::math::lub_constrain(this->read(sizes...), lb, ub, lp); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:443:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 443 | return stan::math::lub_constrain(this->read(sizes...), lb, ub); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::inv_logit_fun; T = Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >]' 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:443:0: required from 'auto stan::io::deserializer::read_constrain_lub(const LB&, const UB&, LP&, Sizes ...) [with Ret = Eigen::Matrix, -1, 1>; bool Jacobian = true; LB = int; UB = int; LP = stan::math::var_value; Sizes = {int}; T = stan::math::var_value]' 443 | return stan::math::lub_constrain(this->read(sizes...), lb, ub); stanExports_stanmarg.h:12970:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12969 | Theta_r_free = in__.template read_constrain_lub< 12970 | Eigen::Matrix, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; VarMat2 = Eigen::Transpose, -1, -1> >; stan::require_all_rev_matrix_t* = 0]' 113 | using op_ret_type = decltype(a.val() + b.val()); stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1> > >::val_Op, const Eigen::Transpose, -1, -1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1> > >::val_Op, const Eigen::Transpose, -1, -1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1> > >::val_Op, const Eigen::Transpose, -1, -1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1> > >::val_Op, const Eigen::Transpose, -1, -1> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1> > >::val_Op, const Eigen::Transpose, -1, -1> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; VarMat2 = Eigen::Transpose, -1, -1> >; stan::require_all_rev_matrix_t* = 0]' 113 | using op_ret_type = decltype(a.val() + b.val()); stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> > >::val_Op, const Eigen::Transpose, -1, -1> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> > >::val_Op, const Eigen::Transpose, -1, -1> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> > >::val_Op, const Eigen::Transpose, -1, -1> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> > >::val_Op, const Eigen::Transpose, -1, -1> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> > >::val_Op, const Eigen::Transpose, -1, -1> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from 'struct stan::is_any_var_matrix, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1, 0, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> > >::val_Op, const Eigen::Transpose, -1, -1, 0, -1, -1> > > >, Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::Transpose, -1, -1, 0, -1, -1> > >' 80 | : bool_constant...>::value> {}; | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> > >::val_Op, const Eigen::Transpose, -1, -1> > > >; Types = {Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::Transpose, -1, -1, 0, -1, -1> >}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; VarMat2 = Eigen::Transpose, -1, -1> >; stan::require_all_rev_matrix_t* = 0]' 114 | using ret_type = return_var_matrix_t; stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; VarMat2 = Eigen::Transpose, -1, -1> >; stan::require_all_rev_matrix_t* = 0]' 117 | arena_t ret(arena_a.val() + arena_b.val()); stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; VarMat2 = Eigen::Transpose, -1, -1> >; stan::require_all_rev_matrix_t* = 0]' 117 | arena_t ret(arena_a.val() + arena_b.val()); stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; VarMat2 = Eigen::Transpose, -1, -1> >; stan::require_all_rev_matrix_t* = 0]' 117 | arena_t ret(arena_a.val() + arena_b.val()); stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1, 1, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; VarMat2 = Eigen::Transpose, -1, -1> >; stan::require_all_rev_matrix_t* = 0]' 123 | arena_b.adj().coeffRef(i, j) += ref_adj; stanExports_stanmarg.h:13361:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 154 | (a.val().array() - as_array_or_scalar(b)).matrix())>; stanExports_stanmarg.h:13360:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 154 | (a.val().array() - as_array_or_scalar(b)).matrix())>; stanExports_stanmarg.h:13360:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: recursively required by substitution of 'template struct stan::plain_type, stan::is_eigen::type> >::value, void>::type> [with T = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > >]' 22 | using plain_type_t = typename plain_type::type; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: required by substitution of 'template using stan::plain_type_t = typename stan::plain_type::type [with T = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > >]' D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 153 | using op_ret_type = plain_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 157 | arena_t ret(arena_a.val().array() - as_array_or_scalar(b)); stanExports_stanmarg.h:13360:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 157 | arena_t ret(arena_a.val().array() - as_array_or_scalar(b)); stanExports_stanmarg.h:13360:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar, 0, Eigen::Stride<0, 0> >&>(const Eigen::Map, 0, Eigen::Stride<0, 0> >&):: [with auto:13 = const Eigen::Map, 0, Eigen::Stride<0, 0> >]' 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 180 | (as_array_or_scalar(a) - b.val().array()).matrix())>; stanExports_stanmarg.h:13574:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 180 | (as_array_or_scalar(a) - b.val().array()).matrix())>; stanExports_stanmarg.h:13574:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: recursively required by substitution of 'template struct stan::plain_type, stan::is_eigen::type> >::value, void>::type> [with T = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > > >]' 22 | using plain_type_t = typename plain_type::type; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: required by substitution of 'template using stan::plain_type_t = typename stan::plain_type::type [with T = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > > >]' D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 179 | using op_ret_type = plain_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 183 | arena_t ret(as_array_or_scalar(a) - arena_b.val().array()); stanExports_stanmarg.h:13574:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 185 | [ret, arena_b]() mutable { arena_b.adj() -= ret.adj_op(); }); stanExports_stanmarg.h:13574:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from 'struct stan::is_any_var_matrix, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1, 0, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1, 0, -1, -1> > >, Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::Matrix, -1, -1, 0, -1, -1> >' 80 | : bool_constant...>::value> {}; | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >; Types = {Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::Matrix, -1, -1, 0, -1, -1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; VarMat2 = Eigen::Matrix, -1, -1>; stan::require_all_rev_matrix_t* = 0]' 114 | using ret_type = return_var_matrix_t; stanExports_stanmarg.h:13615:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; VarMat2 = Eigen::Matrix, -1, -1>; stan::require_all_rev_matrix_t* = 0]' 117 | arena_t ret(arena_a.val() + arena_b.val()); stanExports_stanmarg.h:13615:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from 'struct stan::is_any_var_matrix, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::VectorBlock, -1, -1, 0, -1, -1>, -1, 1, true>, -1> >' 80 | : bool_constant...>::value> {}; | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::VectorBlock, -1, -1, 0, -1, -1>, -1, 1, true>, -1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:36:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 36 | using return_t stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:43:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 43 | arena_A.adj() += res.adj_op() * arena_B_val.transpose(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:47:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 47 | arena_A.adj() += res_adj * arena_B_val.transpose(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of, -1, -1>&>(const Eigen::Matrix, -1, -1>&):: [with auto:11 = const Eigen::Matrix, -1, -1>]' 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:53:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 53 | arena_t> arena_A = value_of(A); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, -1, 1, true>, -1>&>(const Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>&)::::, const Eigen::Block, -1, -1>, -1, 1, true>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, -1, 1, true>, -1>&>(const Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>&)::::, const Eigen::Block, -1, -1>, -1, 1, true>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, -1, 1, true>, -1>&>(const Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>&)::::, const Eigen::Block, -1, -1>, -1, 1, true>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1>, -1, 1, true>, -1>&>(const Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>&)::::, const Eigen::Block, -1, -1>, -1, 1, true>, -1, 1, false>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1>, -1, 1, true>, -1>&>(const Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>&)::::, const Eigen::Block, -1, -1>, -1, 1, true>, -1, 1, false> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of, -1, -1>, -1, 1, true>, -1>&>(const Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>&):: [with auto:11 = const Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>]' 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:56:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 56 | = return_var_matrix_t; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from 'struct stan::is_any_var_matrix, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::VectorBlock, -1, -1, 0, -1, -1>, -1, 1, true>, -1> >' 80 | : bool_constant...>::value> {}; | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>; Types = {Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::VectorBlock, -1, -1, 0, -1, -1>, -1, 1, true>, -1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:55:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 55 | using return_t stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&)::::, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of, -1, -1>, void>&>(arena_matrix, -1, -1>, void>&):: [with auto:11 = stan::math::arena_matrix, -1, -1>, void>]' 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:66:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 66 | = return_var_matrix_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from 'struct stan::is_any_var_matrix, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::VectorBlock, -1, -1, 0, -1, -1>, -1, 1, true>, -1> >' 80 | : bool_constant...>::value> {}; | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::VectorBlock, -1, -1, 0, -1, -1>, -1, 1, true>, -1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:65:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 65 | using return_t stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; VarMat2 = Eigen::Matrix, -1, 1>; stan::require_all_rev_matrix_t* = 0]' 113 | using op_ret_type = decltype(a.val() + b.val()); stanExports_stanmarg.h:13633:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/is_var_matrix.hpp:80:65: required from 'struct stan::is_any_var_matrix, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1, 0, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1, 0, -1, 1> > >, Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Matrix, -1, 1, 0, -1, 1> >' 80 | : bool_constant...>::value> {}; | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> >, const Eigen::CwiseUnaryOp, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Matrix, -1, 1, 0, -1, 1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; VarMat2 = Eigen::Matrix, -1, 1>; stan::require_all_rev_matrix_t* = 0]' 114 | using ret_type = return_var_matrix_t; stanExports_stanmarg.h:13633:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; VarMat2 = Eigen::Matrix, -1, 1>; stan::require_all_rev_matrix_t* = 0]' 117 | arena_t ret(arena_a.val() + arena_b.val()); stanExports_stanmarg.h:13633:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 169 | return add(b, a); stanExports_stanmarg.h:14697:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 169 | return add(b, a); stanExports_stanmarg.h:14697:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 148 | using ret_type = return_var_matrix_t; D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 169 | return add(b, a); stanExports_stanmarg.h:14697:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 150 | arena_t ret(arena_a.val().array() + as_array_or_scalar(b)); D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 169 | return add(b, a); stanExports_stanmarg.h:14697:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 145 | arena_t res = arena_A.val() * arena_B.val().array(); stanExports_stanmarg.h:14696:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 163 | arena_B.adj().array() += arena_A * res.adj().array(); stanExports_stanmarg.h:14696:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 170 | arena_t res = arena_A.val() * arena_B.array(); stanExports_stanmarg.h:14696:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 170 | arena_t res = arena_A.val() * arena_B.array(); stanExports_stanmarg.h:14696:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 172 | arena_A.adj() += (res.adj().array() * arena_B.array()).sum(); stanExports_stanmarg.h:14696:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Transpose > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Transpose > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Transpose > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, Eigen::Transpose >, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, Eigen::Transpose > >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:40:13: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(A) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | .transpose() | ~~~~~~~~~~~~ 39 | .lu() | ~~~~~ 40 | .solve(Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Transpose > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Transpose > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Transpose > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, Eigen::Transpose > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >, Eigen::Transpose > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:42:17: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(A) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | .transpose() | ~~~~~~~~~~~~ 39 | .lu() | ~~~~~ 40 | .solve(Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::Matrix, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:26: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::Matrix, 0>, Eigen::Matrix, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::Matrix, 0>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:34: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:36:40: required from 'stan::math::quad_form_sym, Eigen::Matrix >(const Eigen::Matrix&, const Eigen::Matrix&):: [with auto:377 = Eigen::Matrix]' 36 | [](const auto& ret) { return 0.5 * (ret + ret.transpose()); }, | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::quad_form_sym, Eigen::Matrix >(const Eigen::Matrix&, const Eigen::Matrix&)::; Args = {const Eigen::Matrix}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:35:21: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:115:7: required from 'class stan::math::Holder, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >, const Eigen::Matrix >' 115 | class Holder | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const std::tuple&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >; long long unsigned int ...Is = {0}; Args = {const Eigen::Matrix}; std::index_sequence = std::integer_sequence]' 312 | return holder(std::forward(expr), std::get(ptrs)...); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:330:43: required from 'auto stan::math::internal::make_holder_impl(const F&, std::index_sequence, Args&& ...) [with F = stan::math::quad_form_sym, Eigen::Matrix >(const Eigen::Matrix&, const Eigen::Matrix&)::; long long unsigned int ...Is = {0}; Args = {const Eigen::Matrix}; std::index_sequence = std::integer_sequence]' 330 | return make_holder_impl_construct_object( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 331 | func(*std::get(res)...), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 332 | std::make_index_sequence::value>(), ptrs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >(const Eigen::Matrix&, const Eigen::Matrix&)::; Args = {const Eigen::Matrix}; stan::require_not_plain_type_t()((declval)()...))>* = 0]' 353 | return internal::make_holder_impl(func, | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ 354 | std::make_index_sequence(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 355 | std::forward(args)...); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:35:21: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Matrix, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:26: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:34: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Transpose > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Transpose > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Transpose > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Transpose >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:36:47: required from 'stan::math::quad_form_sym, Eigen::Transpose > >(const Eigen::Matrix&, const Eigen::Transpose >&):: [with auto:377 = Eigen::Matrix]' 36 | [](const auto& ret) { return 0.5 * (ret + ret.transpose()); }, | ~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::quad_form_sym, Eigen::Transpose > >(const Eigen::Matrix&, const Eigen::Transpose >&)::; Args = {const Eigen::Matrix}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:35:21: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:36:40: required from 'stan::math::quad_form_sym, Eigen::Transpose > >(const Eigen::Matrix&, const Eigen::Transpose >&):: [with auto:377 = Eigen::Matrix]' 36 | [](const auto& ret) { return 0.5 * (ret + ret.transpose()); }, | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::quad_form_sym, Eigen::Transpose > >(const Eigen::Matrix&, const Eigen::Transpose >&)::; Args = {const Eigen::Matrix}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:35:21: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:115:7: required from 'class stan::math::Holder, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >, const Eigen::Matrix >' 115 | class Holder | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const std::tuple&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >; long long unsigned int ...Is = {0}; Args = {const Eigen::Matrix}; std::index_sequence = std::integer_sequence]' 312 | return holder(std::forward(expr), std::get(ptrs)...); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:330:43: required from 'auto stan::math::internal::make_holder_impl(const F&, std::index_sequence, Args&& ...) [with F = stan::math::quad_form_sym, Eigen::Transpose > >(const Eigen::Matrix&, const Eigen::Transpose >&)::; long long unsigned int ...Is = {0}; Args = {const Eigen::Matrix}; std::index_sequence = std::integer_sequence]' 330 | return make_holder_impl_construct_object( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 331 | func(*std::get(res)...), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 332 | std::make_index_sequence::value>(), ptrs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::Transpose > >(const Eigen::Matrix&, const Eigen::Transpose >&)::; Args = {const Eigen::Matrix}; stan::require_not_plain_type_t()((declval)()...))>* = 0]' 353 | return internal::make_holder_impl(func, | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ 354 | std::make_index_sequence(), | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 355 | std::forward(args)...); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:35:21: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Ref.h:59:34: required from 'class Eigen::RefBase, 0, Eigen::OuterStride<> > >' 59 | template class RefBase | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Ref.h:329:77: required from 'class Eigen::Ref, 0, Eigen::OuterStride<> >' 329 | template class Ref | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:31:49: required from 'Eigen::Matrix::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix; typename stan::value_type::type = double]' 31 | const Eigen::Ref>& 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::OuterStride<> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::OuterStride<> > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:33:60: required from 'Eigen::Matrix::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix; typename stan::value_type::type = double]' 33 | plain_type_t 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Ref, 0, Eigen::OuterStride<> >, const Eigen::Transpose, 0, Eigen::OuterStride<> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Ref, 0, Eigen::OuterStride<> >, const Eigen::Transpose, 0, Eigen::OuterStride<> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Ref, 0, Eigen::OuterStride<> >, const Eigen::Transpose, 0, Eigen::OuterStride<> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Ref, 0, Eigen::OuterStride<> >, const Eigen::Transpose, 0, Eigen::OuterStride<> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Ref, 0, Eigen::OuterStride<> >, const Eigen::Transpose, 0, Eigen::OuterStride<> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:33:43: required from 'Eigen::Matrix::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix; typename stan::value_type::type = double]' 33 | plain_type_t 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Ref, 0, Eigen::OuterStride<> >, const Eigen::Transpose, 0, Eigen::OuterStride<> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Ref, 0, Eigen::OuterStride<> >, const Eigen::Transpose, 0, Eigen::OuterStride<> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Ref, 0, Eigen::OuterStride<> >, const Eigen::Transpose, 0, Eigen::OuterStride<> > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Ref, 0, Eigen::OuterStride<> >, const Eigen::Transpose, 0, Eigen::OuterStride<> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Ref, 0, Eigen::OuterStride<> >, const Eigen::Transpose, 0, Eigen::OuterStride<> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:33:34: required from 'Eigen::Matrix::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix; typename stan::value_type::type = double]' 33 | plain_type_t 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseNullaryOp, Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseNullaryOp, Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseNullaryOp, Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, Eigen::CwiseNullaryOp, Eigen::Matrix >, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, Eigen::CwiseNullaryOp, Eigen::Matrix > >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:44:20: required from 'Eigen::Matrix::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix; typename stan::value_type::type = double]' 44 | return ldlt.solve( | ~~~~~~~~~~^ 45 | Eigen::Matrix::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Product >, Eigen::Matrix, 0>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 - m2; | ~~~^~~~ stanExports_stanmarg.h:4436:0: required from 'Eigen::Matrix::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T4__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_cholesky_rng.hpp:72:55: required from 'typename stan::StdVectorBuilder, T_loc>::type stan::math::multi_normal_cholesky_rng(const T_loc&, const Eigen::Matrix&, RNG&) [with T_loc = Eigen::Matrix; RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; typename stan::StdVectorBuilder, T_loc>::type = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Matrix >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:513:38: required from 'struct Eigen::internal::cast_return_type, const Eigen::CwiseUnaryOp, const Eigen::Matrix > >' 513 | typedef typename _CastType::Scalar NewScalarType; | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/plugins/CommonCwiseUnaryOps.h:48:179: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T2 = Eigen::Matrix; = void]' 49 | result.leftCols(Acols) = A.template cast(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ stanExports_stanmarg.h:2847:0: required from 'Eigen::Matrix::type, typename stan::base_type::type>::type, -1, -1> model_stanmarg_namespace::calc_B_tilde(const T0__&, const T1__&, const std::vector&, const int&, std::ostream*) [with T0__ = Eigen::Matrix; T1__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Matrix >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:513:38: required from 'struct Eigen::internal::cast_return_type, const Eigen::CwiseUnaryOp, const Eigen::Matrix > >' 513 | typedef typename _CastType::Scalar NewScalarType; | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/plugins/CommonCwiseUnaryOps.h:48:179: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T2 = Eigen::Matrix; = void]' 50 | result.rightCols(Bcols) = B.template cast(); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~ stanExports_stanmarg.h:2847:0: required from 'Eigen::Matrix::type, typename stan::base_type::type>::type, -1, -1> model_stanmarg_namespace::calc_B_tilde(const T0__&, const T1__&, const std::vector&, const int&, std::ostream*) [with T0__ = Eigen::Matrix; T1__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:4576:0: required from 'std::vector::type, -1, 1> > model_stanmarg_namespace::calc_mean_vecs(const std::vector >&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; stan::require_all_t, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Block, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Block, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Block, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Block, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Block, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::VectorBlock, -1>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:4600:0: required from 'std::vector::type, -1, 1> > model_stanmarg_namespace::calc_mean_vecs(const std::vector >&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; stan::require_all_t, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Block, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Block, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Block, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Block, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; Mat2 = Eigen::VectorBlock, -1>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 - m2; | ~~~^~~~ stanExports_stanmarg.h:4696:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::calc_cov_mats(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::VectorBlock, -1>; Mat2 = Eigen::VectorBlock, -1>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 - m2; | ~~~^~~~ stanExports_stanmarg.h:4740:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::calc_cov_mats(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0>; Mat2 = Eigen::Transpose >; stan::require_all_eigen_vt* = 0; stan::require_not_eigen_row_and_col_t* = 0]' 107 | return m1 * m2; | ~~~^~~~ stanExports_stanmarg.h:4183:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 - m2; | ~~~^~~~ stanExports_stanmarg.h:4182:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::VectorBlock, -1>; Mat2 = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 - m2; | ~~~^~~~ stanExports_stanmarg.h:4201:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0>; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >; stan::require_all_eigen_vt* = 0; stan::require_not_eigen_row_and_col_t* = 0]' 107 | return m1 * m2; | ~~~^~~~ stanExports_stanmarg.h:4200:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; Mat2 = Eigen::Product, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:4193:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Product, Eigen::Transpose >, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Product, Eigen::Transpose >, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Product, Eigen::Transpose >, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Product, Eigen::Transpose >, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, Eigen::Transpose >, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::Product, Eigen::Transpose >, 0>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 - m2; | ~~~^~~~ stanExports_stanmarg.h:3277:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Mat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:3396:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::Matrix, 0>; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0; stan::require_all_not_complex_t::type>* = 0]' 84 | return c * m; | ~~^~~ stanExports_stanmarg.h:3415:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:3414:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Mat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 28 | return m1.cwiseProduct(m2); | ~~~~~~~~~~~~~~~^~~~ stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; Mat2 = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 - m2; | ~~~^~~~ stanExports_stanmarg.h:3450:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/multiply.hpp:28:12: required from 'auto stan::math::multiply(const Mat&, Scal) [with Mat = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Scal = double; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0; stan::require_all_not_complex_t::type>* = 0]' 28 | return c * m; | ~~^~~ stanExports_stanmarg.h:3486:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:3501:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; Mat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:3500:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >; Mat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:3499:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, const Eigen::Matrix >, const Eigen::Matrix >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0; stan::require_all_not_complex_t::type>* = 0]' 84 | return c * m; | ~~^~~ stanExports_stanmarg.h:3498:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Mat2 = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:3507:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0; stan::require_all_not_complex_t::type>* = 0]' 84 | return c * m; | ~~^~~ stanExports_stanmarg.h:3513:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Matrix; Mat2 = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:3512:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Core:277: D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from 'struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, -1, 1, false> >' 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from 'struct stan::ref_type_if, -1>&, void>' 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of 'template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::VectorBlock, -1>&]' 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of 'template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::VectorBlock, -1>&]' 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_stanmarg.h:4478:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from 'struct Eigen::internal::traits, 0, Eigen::OuterStride<> > >::match, -1, -1, false> >' 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from 'struct stan::ref_type_if, -1, -1, false>&, void>' 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of 'template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::Block, -1, -1, false>&]' 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of 'template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Block, -1, -1, false>&]' 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_stanmarg.h:4479:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, false>, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/subtract.hpp:45:13: required from 'auto stan::math::subtract(const Mat1&, const Mat2&) [with Mat1 = Eigen::VectorBlock, -1>; Mat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 - m2; | ~~~^~~~ stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/transpose.hpp:18:21: required from 'auto stan::math::transpose(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >; stan::require_matrix_t* = 0]' 18 | return m.transpose(); | ~~~~~~~~~~~^~ stanExports_stanmarg.h:4503:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from 'auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >; Mat2 = Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >; stan::require_all_eigen_vt* = 0; stan::require_not_eigen_row_and_col_t* = 0]' 107 | return m1 * m2; | ~~~^~~~ stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Block, -1, -1, false>; Mat2 = Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:4501:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 28 | return m1.cwiseProduct(m2); | ~~~~~~~~~~~~~~~^~~~ stanExports_stanmarg.h:4497:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/multiply.hpp:107:13: required from 'auto stan::math::multiply(const Mat1&, const Mat2&) [with Mat1 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Mat2 = Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >; stan::require_all_eigen_vt* = 0; stan::require_not_eigen_row_and_col_t* = 0]' 107 | return m1 * m2; | ~~~^~~~ stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Block, -1, -1, false>; Mat2 = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:4501:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 28 | return m1.cwiseProduct(m2); | ~~~~~~~~~~~~~~~^~~~ stanExports_stanmarg.h:4497:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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]' 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:35:15: required from 'stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]' 35 | check_finite("hypergeometric_pFq", "a", a_ref); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from 'stan::return_type_t 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; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]' 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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]' 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >* = 0]' 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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]' 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:36:15: required from 'stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]' 36 | check_finite("hypergeometric_pFq", "b", b_ref); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from 'stan::return_type_t 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; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]' 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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]' 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >* = 0]' 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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]' 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:39:16: required from 'stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]' 39 | check_not_nan("hypergeometric_pFq", "a", a_ref); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from 'stan::return_type_t 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; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]' 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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]' 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >* = 0]' 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >(const char*, const char*, const Eigen::Matrix&)::; T = Eigen::Matrix; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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]' 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/hypergeometric_pFq.hpp:40:16: required from 'stan::return_type_t stan::math::hypergeometric_pFq(const Ta&, const Tb&, const Tz&) [with Ta = Eigen::Matrix; Tb = Eigen::Matrix; Tz = double; stan::require_all_eigen_st* = 0; stan::require_arithmetic_t* = 0; stan::return_type_t = double]' 40 | check_not_nan("hypergeometric_pFq", "b", b_ref); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/hypergeometric_2F1.hpp:189:30: required from 'stan::return_type_t 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; stan::require_all_arithmetic_t* = 0; stan::return_type_t = double]' 189 | return hypergeometric_pFq(a_args, b_args, z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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]' 190 | auto hyper1 = hypergeometric_2F1(a1_euler, a2_euler, b1, z_euler); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >* = 0]' 306 | return internal::grad_2F1_impl(a1, a2, b1, z, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ 307 | precision, max_steps); | ~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/grad_inc_beta.hpp:37:25: required from here 37 | = grad_2F1(a + b, 1.0, a + 1, z); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, member_sum, 1>; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 2, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix >, 2, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix >, 2, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::Matrix >, 2, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::Matrix >, 2, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::Matrix >, 2, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:203:15: required from 'PacketType Eigen::internal::evaluator >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Eigen::Index = long long int]' 203 | PanelType panel(m_arg, | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]' 251 | PacketScalar packet_res0 = eval.template packet(alignedStart); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::Matrix >, 2, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Matrix >, 2, -1, true> >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:217:20: required from 'PacketType Eigen::internal::evaluator >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Eigen::Index = long long int]' 217 | PanelEvaluator panel_eval(panel); | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]' 251 | PacketScalar packet_res0 = eval.template packet(alignedStart); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix >, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix >, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::Matrix >, 1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::Matrix >, 1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::Matrix >, 1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:72: required from 'const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Scalar = double; Eigen::Index = long long int]' 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]' 268 | res = func(res,eval.coeff(index)); | ~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gemm_pack_rhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long long int; DataMapper = Eigen::internal::const_blas_data_mapper; int nr = 4; bool Conjugate = false; bool PanelMode = false]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:100:15: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]' 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]' 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 2459 | PacketBlock kernel; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long long int; DataMapper = Eigen::internal::const_blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = false]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:106:17: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]' 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]' 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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::half>::half QuarterPacket; | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::size, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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::size, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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 kernel_half; | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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 kernel_quarter; | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gebp_kernel::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; int mr = 4; int nr = 4; bool ConjugateLhs = false; bool ConjugateRhs = false; ResScalar = double]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:113:15: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]' 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]' 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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::half>::size; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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::half>::half>::size; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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=8,typename unpacket_traits::half,SResPacket>::type SResPacketHalf; | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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=8,typename unpacket_traits::half,SLhsPacket>::type SLhsPacketHalf; | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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=8,typename unpacket_traits::half,SRhsPacket>::type SRhsPacketHalf; | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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=8,typename unpacket_traits::half,SAccPacket>::type SAccPacketHalf; | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits >' 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix' 178 | class Matrix | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:155:52: required from 'void Eigen::internal::tribb_kernel::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 buffer((internal::constructor_without_unaligned_array_assert())); | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]' 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]' 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]' 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]' 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Matrix; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/variance.hpp:28:0: required from here 28 | double variance = diff.squaredNorm() / size_m1; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:370:46: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:370:35: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0>, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0>, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0>, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, 0>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, 0>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, 0>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 0>, -1, 1, false>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Block, 0>, -1, 1, false> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 352 | Block A21(mat,k+1,k,rs,1); | ^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 358 | temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0>, -1, 1, false> >, Eigen::Transpose, 1, -1, false> >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 358 | temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false>, Eigen::Block, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Block, -1, 1, false>, 0, 6>' 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 1, -1, false>, Eigen::Block, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 359 | mat.coeffRef(k,k) -= (A10 * temp.head(k)).value(); | ~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1, true>, -1, 1, false> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, 1, true>, -1, 1, false> >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 379 | ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1, false> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, 1, false> >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 387 | ret = ret && (A21.array()==Scalar(0)).all(); | ~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<1> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<1> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::InnerStride<1> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::InnerStride<1> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::InnerStride<1> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map, 0, Eigen::InnerStride<1> >' 94 | template class Map | ^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:887:41: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:120:49: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_L(const T&, size_t, stan::value_type_t&) [with T = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int; stan::value_type_t = double]' 120 | acc += (K - k - 1) * log1m(square(CPCs_ref(pos))); | ~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:55: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t&) [with T_CPCs = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int; stan::value_type_t = double]' 61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; stan::require_eigen_matrix_dynamic_t* = 0; stan::require_not_st_autodiff* = 0; matrix_d = Eigen::Matrix]' 37 | LLt(n, m) = LLt(m, n) = Lt.col(m).head(k).dot(Lt.col(n).head(k)); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:43: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t&) [with T_CPCs = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int; stan::value_type_t = double]' 61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, 0, Eigen::OuterStride<> >, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 32 | sds = Sigma_ref.diagonal().array(); | ~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::OuterStride<> >, 0> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, 0, Eigen::OuterStride<> >, 0> >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 32 | sds = Sigma_ref.diagonal().array(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Array >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 36 | sds = sds.sqrt(); | ~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Array >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 39 | D.diagonal() = sds.inverse(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Array >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 40 | sds = sds.log(); // now unbounded | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Ref, 0, Eigen::OuterStride<> >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Ref, 0, Eigen::OuterStride<> >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Ref, 0, Eigen::OuterStride<> >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Ref, 0, Eigen::OuterStride<> >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Ref, 0, Eigen::OuterStride<> >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Ref, 0, Eigen::OuterStride<> >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 42 | Eigen::Matrix R = D * Sigma_ref * D; | ~~^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Ref, 0, Eigen::OuterStride<> >, 1>, Eigen::DiagonalMatrix, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Ref, 0, Eigen::OuterStride<> >, 1>, Eigen::DiagonalMatrix, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Ref, 0, Eigen::OuterStride<> >, 1>, Eigen::DiagonalMatrix, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Ref, 0, Eigen::OuterStride<> >, 1>, Eigen::DiagonalMatrix, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Ref, 0, Eigen::OuterStride<> >, 1>, Eigen::DiagonalMatrix, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Ref, 0, Eigen::OuterStride<> >, 1>, Eigen::DiagonalMatrix, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 42 | Eigen::Matrix R = D * Sigma_ref * D; | ~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >(Eigen::Matrix&&, const char*, const index_multi&)::::, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >(Eigen::Matrix&&, const char*, const index_multi&)::::, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >(Eigen::Matrix&&, const char*, const index_multi&)::::, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp >(Eigen::Matrix&&, const char*, const index_multi&)::::, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:158:0: required from 'stan::model::rvalue >(Eigen::Matrix&&, const char*, const index_multi&):: [with auto:767 = Eigen::Matrix]' 158 | return plain_type_t::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/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::model::rvalue >(Eigen::Matrix&&, const char*, const index_multi&)::; Args = {Eigen::Matrix&}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 77 | return (c + m.array()).matrix(); | ~~~^~~~~~~~~~~~ stanExports_stanmarg.h:14697:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 77 | return (c + m.array()).matrix(); | ~~~~~~~~~~~~~~~~~~~~~~^~ stanExports_stanmarg.h:14697:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >; stan::require_stan_scalar_t* = 0; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0; stan::require_all_not_complex_t::type>* = 0]' 84 | return c * m; | ~~^~~ stanExports_stanmarg.h:14696:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Scalar = double; XType = Eigen::Matrix]' 247 | x1.noalias() = x0 + alpha1 * p; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:209:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; 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/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, Eigen::Matrix >, const Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:34:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 34 | = HessianT::Identity(yk.size(), yk.size()) - rhok * sk * yk.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 40 | _Hk = Hupd * _Hk * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Product, Eigen::Matrix, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Product, Eigen::Matrix, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Product, Eigen::Matrix, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Product, Eigen::Matrix, 0> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:55:0: required from 'void stan::optimization::BFGSUpdate_HInv::search_direction(VectorT&, const VectorT&) const [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 55 | pk.noalias() = -(_Hk * gk); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:254:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 254 | _qn.search_direction(_pk, _gk); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Inverse.h:68:7: required from 'class Eigen::InverseImpl >, Eigen::SolverStorage>' 68 | class InverseImpl | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Inverse.h:43:7: required from 'class Eigen::Inverse > >' 43 | class Inverse : public InverseImpl::StorageKind> | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; stan::require_rev_matrix_t* = 0; var = var_value]' 23 | auto arena_m_inv_transpose = to_arena(m_hh.inverse().transpose()); stanExports_stanmarg.h:14144:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; stan::require_rev_matrix_t* = 0; var = var_value]' 23 | auto arena_m_inv_transpose = to_arena(m_hh.inverse().transpose()); stanExports_stanmarg.h:14144:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; stan::require_rev_matrix_t* = 0; var = var_value]' 27 | arena_m.adj() += log_det.adj() * arena_m_inv_transpose; stanExports_stanmarg.h:14144:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1> >&>(const Eigen::Transpose, -1, -1> >&)::::, const Eigen::Transpose, -1, -1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1> >&>(const Eigen::Transpose, -1, -1> >&)::::, const Eigen::Transpose, -1, -1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1> >&>(const Eigen::Transpose, -1, -1> >&)::::, const Eigen::Transpose, -1, -1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1> >&>(const Eigen::Transpose, -1, -1> >&)::::, const Eigen::Transpose, -1, -1> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1> >&>(const Eigen::Transpose, -1, -1> >&)::::, const Eigen::Transpose, -1, -1> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of, -1, -1> >&>(const Eigen::Transpose, -1, -1> >&):: [with auto:11 = const Eigen::Transpose, -1, -1> >]' 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>; Types = {Eigen::Transpose, -1, -1, 0, -1, -1> >, Eigen::Matrix, -1, -1, 0, -1, -1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:55:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Transpose, -1, -1> >; T2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 55 | using return_t stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Transpose, -1, -1, 0, -1, -1> >, Eigen::Matrix, -1, -1, 0, -1, -1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:65:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Transpose, -1, -1> >; T2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 65 | using return_t stanExports_stanmarg.h:4444:0: required from 'Eigen::Matrix::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >; Types = {Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::Matrix, -1, -1, 0, -1, -1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; VarMat2 = Eigen::Matrix, -1, -1>; stan::require_all_rev_matrix_t* = 0]' 121 | using ret_type = return_var_matrix_t; stanExports_stanmarg.h:4436:0: required from 'Eigen::Matrix::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; VarMat2 = Eigen::Matrix, -1, -1>; stan::require_all_rev_matrix_t* = 0]' 124 | arena_t ret((arena_a.val() - arena_b.val())); stanExports_stanmarg.h:4436:0: required from 'Eigen::Matrix::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>; Types = {Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::Transpose, -1, -1, 0, -1, -1> >}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:55:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::Transpose, -1, -1> >; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 55 | using return_t stanExports_stanmarg.h:3278:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3278 | stan::math::multiply(Sigma_yz, stan::math::transpose(Sigma_yz_zi))), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 180 | (as_array_or_scalar(a) - b.val().array()).matrix())>; stanExports_stanmarg.h:3309:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > > >' 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: recursively required by substitution of 'template struct stan::plain_type, stan::is_eigen::type> >::value, void>::type> [with T = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > >]' 22 | using plain_type_t = typename plain_type::type; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: required by substitution of 'template using stan::plain_type_t = typename stan::plain_type::type [with T = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > >]' D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 179 | using op_ret_type = plain_type_t::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 183 | arena_t ret(as_array_or_scalar(a) - arena_b.val().array()); stanExports_stanmarg.h:3309:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_stanmarg.h:3351:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > > >' 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper > > >; Types = {Eigen::Matrix, -1, -1, 0, -1, -1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 148 | using ret_type = return_var_matrix_t; stanExports_stanmarg.h:3351:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 150 | arena_t ret(arena_a.val().array() + as_array_or_scalar(b)); stanExports_stanmarg.h:3351:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, const Eigen::Array >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 38 | >::type Scalar; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 145 | arena_t res = arena_A.val() * arena_B.val().array(); stanExports_stanmarg.h:3396:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 163 | arena_B.adj().array() += arena_A * res.adj().array(); stanExports_stanmarg.h:3396:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 170 | arena_t res = arena_A.val() * arena_B.array(); stanExports_stanmarg.h:3396:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; stan::require_not_matrix_t* = 0; stan::require_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 172 | arena_A.adj() += (res.adj().array() * arena_B.array()).sum(); stanExports_stanmarg.h:3396:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3396 | stan::math::add(stan::math::multiply(nj, Sigma_b_z), Sigma_w), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >; Types = {Eigen::Matrix, -1, -1, 0, -1, -1>, Eigen::Matrix, -1, -1, 0, -1, -1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; Mat2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]' 31 | using ret_type = return_var_matrix_t; stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; Mat2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]' 35 | arena_t ret(arena_m1.val().cwiseProduct(arena_m2.val())); stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; Mat2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]' 49 | arena_t ret(arena_m1.val().cwiseProduct(arena_m2)); stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; Mat2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]' 51 | arena_m1.adj().array() += arena_m2.array() * ret.adj().array(); stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; Mat2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]' 57 | arena_t ret(arena_m1.cwiseProduct(arena_m2.val())); stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 154 | (a.val().array() - as_array_or_scalar(b)).matrix())>; stanExports_stanmarg.h:3487:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3487 | stan::math::subtract(nperclus, stan::math::to_vector(clus_size_ns)), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > > >' 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: recursively required by substitution of 'template struct stan::plain_type, stan::is_eigen::type> >::value, void>::type> [with T = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > >]' 22 | using plain_type_t = typename plain_type::type; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: required by substitution of 'template using stan::plain_type_t = typename stan::plain_type::type [with T = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper > > >]' D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 153 | using op_ret_type = plain_type_t::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3487 | stan::math::subtract(nperclus, stan::math::to_vector(clus_size_ns)), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 157 | arena_t ret(arena_a.val().array() - as_array_or_scalar(b)); stanExports_stanmarg.h:3487:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3487 | stan::math::subtract(nperclus, stan::math::to_vector(clus_size_ns)), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, const Eigen::Matrix >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Matrix}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; Mat2 = Eigen::Matrix; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]' 31 | using ret_type = return_var_matrix_t; stanExports_stanmarg.h:3502:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; Mat2 = Eigen::Matrix; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]' 35 | arena_t ret(arena_m1.val().cwiseProduct(arena_m2.val())); stanExports_stanmarg.h:3502:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; Mat2 = Eigen::Matrix; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]' 49 | arena_t ret(arena_m1.val().cwiseProduct(arena_m2)); stanExports_stanmarg.h:3502:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; Mat2 = Eigen::Matrix; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]' 51 | arena_m1.adj().array() += arena_m2.array() * ret.adj().array(); stanExports_stanmarg.h:3502:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>; Mat2 = Eigen::Matrix; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]' 57 | arena_t ret(arena_m1.cwiseProduct(arena_m2.val())); stanExports_stanmarg.h:3502:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 3502 | stan::math::elt_multiply(L, stan::math::to_vector(clus_size_ns)), stanExports_stanmarg.h:14275:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >&>(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >&):: [with auto:13 = const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >]' 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >&>(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >&)::; Args = {const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >&}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 147 | = decltype((a.val().array() + as_array_or_scalar(b)).matrix()); stanExports_stanmarg.h:3507:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > > >' 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/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, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 148 | using ret_type = return_var_matrix_t; stanExports_stanmarg.h:3507:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 150 | arena_t ret(arena_a.val().array() + as_array_or_scalar(b)); stanExports_stanmarg.h:3507:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, const Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_ldlt.hpp:32:0: required from 'auto stan::math::mdivide_left_ldlt(LDLT_factor&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::Matrix; stan::require_all_matrix_t* = 0; stan::require_any_st_var* = 0]' 32 | check_multiplicable("mdivide_left_ldlt", "A", A.matrix().val(), "B", B); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_ldlt.hpp:41:0: required from 'auto stan::math::mdivide_left_ldlt(LDLT_factor&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::Matrix; stan::require_all_matrix_t* = 0; stan::require_any_st_var* = 0]' 41 | arena_t res = A.ldlt().solve(arena_B.val()); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_ldlt.hpp:45:0: required from 'auto stan::math::mdivide_left_ldlt(LDLT_factor&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::Matrix; stan::require_all_matrix_t* = 0; stan::require_any_st_var* = 0]' 45 | promote_scalar_t adjB = ldlt_ptr->solve(res.adj()); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from 'struct Eigen::internal::traits, 0, Eigen::InnerStride<1> > >::match, -1, 1, false> >' 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from 'struct stan::ref_type_if, -1>&, void>' 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of 'template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::VectorBlock, -1>&]' 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of 'template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::VectorBlock, -1>&]' 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_stanmarg.h:4478:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 4478 | const auto& xbar = stan::math::to_ref(xbar_arg__); stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from 'struct Eigen::internal::traits, 0, Eigen::OuterStride<> > >::match, -1, -1, false> >' 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:42:38: required from 'struct stan::ref_type_if, -1, -1, false>&, void>' 42 | template match::MatchAtCompileTime | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/ref_type.hpp:54:7: required by substitution of 'template using stan::ref_type_t = typename stan::ref_type_if::type [with T = const Eigen::Block, -1, -1, false>&]' 54 | using ref_type_t = typename ref_type_if::type; | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:17:24: required by substitution of 'template stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Block, -1, -1, false>&]' 17 | inline ref_type_t to_ref(T&& a) { | ^~~~~~ stanExports_stanmarg.h:4479:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 4479 | const auto& S = stan::math::to_ref(S_arg__); stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1, false> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, 1, false> >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar, -1>&>(const Eigen::VectorBlock, -1>&):: [with auto:13 = const Eigen::VectorBlock, -1>]' 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 4502 | stan::math::multiply(stan::math::subtract(xbar, Mu), stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1>; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 180 | (as_array_or_scalar(a) - b.val().array()).matrix())>; stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 4502 | stan::math::multiply(stan::math::subtract(xbar, Mu), stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > > >' 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: recursively required by substitution of 'template struct stan::plain_type, stan::is_eigen::type> >::value, void>::type> [with T = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > >]' 22 | using plain_type_t = typename plain_type::type; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/plain_type.hpp:22:7: required by substitution of 'template using stan::plain_type_t = typename stan::plain_type::type [with T = const Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1> >::val_Op, const Eigen::Matrix, -1, 1> > > > >]' D:/RCompile/CRANpkg/lib/4.5/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, -1>; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 179 | using op_ret_type = plain_type_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 4502 | stan::math::multiply(stan::math::subtract(xbar, Mu), stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::ArrayWrapper, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1>; VarMat = Eigen::Matrix, -1, 1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 183 | arena_t ret(as_array_or_scalar(a) - arena_b.val().array()); stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 4502 | stan::math::multiply(stan::math::subtract(xbar, Mu), stanExports_stanmarg.h:14485:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Transpose, -1, 1, 0, -1, 1> >}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:36:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, 1>; T2 = Eigen::Transpose, -1, 1> >; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 36 | using return_t stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1> >&>(const Eigen::Transpose, -1, 1> >&)::::, const Eigen::Transpose, -1, 1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1> >&>(const Eigen::Transpose, -1, 1> >&)::::, const Eigen::Transpose, -1, 1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1> >&>(const Eigen::Transpose, -1, 1> >&)::::, const Eigen::Transpose, -1, 1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, 1> >&>(const Eigen::Transpose, -1, 1> >&)::::, const Eigen::Transpose, -1, 1> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, 1> >&>(const Eigen::Transpose, -1, 1> >&)::::, const Eigen::Transpose, -1, 1> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of, -1, 1> >&>(const Eigen::Transpose, -1, 1> >&):: [with auto:11 = const Eigen::Transpose, -1, 1> >]' 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Matrix, 0>; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Transpose, -1, 1, 0, -1, 1> >}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:55:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, 1>; T2 = Eigen::Transpose, -1, 1> >; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 55 | using return_t stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, 1>; T2 = Eigen::Transpose, -1, 1> >; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, 1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, 1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; Types = {Eigen::Matrix, -1, 1, 0, -1, 1>, Eigen::Transpose, -1, 1, 0, -1, 1> >}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:65:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, 1>; T2 = Eigen::Transpose, -1, 1> >; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 65 | using return_t stanExports_stanmarg.h:4502:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, -1, false> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, -1, false> >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar, -1, -1, false>&>(const Eigen::Block, -1, -1, false>&):: [with auto:13 = const Eigen::Block, -1, -1, false>]' 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper, -1, -1, false> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper, -1, -1, false> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper, -1, -1, false> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper, -1, -1, false> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper, -1, -1, false> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper, -1, -1, false> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper, -1, -1, false> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper, -1, -1, false> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:140:7: required from 'class Eigen::MatrixWrapper, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper, -1, -1, false> > > >' 140 | class MatrixWrapper : public MatrixBase > | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/is_base_pointer_convertible.hpp:29:17: required from 'struct stan::is_base_pointer_convertible, const Eigen::ArrayWrapper, -1, -1> >::val_Op, const Eigen::Matrix, -1, -1> > >, const Eigen::ArrayWrapper, -1, -1, false> > > > >' 29 | = decltype(f(std::declval *>()))::value | ~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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, -1, -1, false>; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 148 | using ret_type = return_var_matrix_t; D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; VarMat = Eigen::Matrix, -1, -1>; stan::require_st_arithmetic* = 0; stan::require_rev_matrix_t* = 0]' 169 | return add(b, a); stanExports_stanmarg.h:4501:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, -1, false> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, -1, false> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, -1, false> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, -1, false> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper, -1, -1, false> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>&):: [with auto:11 = const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>]' 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false>, -1, -1, false> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >; Types = {Eigen::Block, -1, -1, 0, -1, -1>, -1, -1, false>, -1, -1, false>, Eigen::Matrix, -1, -1, 0, -1, -1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>, -1, -1, false>, -1, -1, false>; Mat2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]' 31 | using ret_type = return_var_matrix_t; stanExports_stanmarg.h:4497:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of, -1, -1>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>&):: [with auto:11 = const Eigen::Block, -1, -1>, -1, -1, false>]' 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T1__ = Eigen::Matrix; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/meta/return_var_matrix.hpp:23:0: required by substitution of 'template using stan::return_var_matrix_t = std::conditional_t<((bool)stan::is_any_var_matrix::value), stan::math::var_value::type>::type, void>::type>, typename stan::math::promote_scalar_type, typename std::decay::type>::type, void>::type> [with ReturnType = const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1>, -1, -1, false>&>(const Eigen::Block, -1, -1>, -1, -1, false>&)::::, const Eigen::Block, -1, -1>, -1, -1, false> >, const Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >; Types = {Eigen::Block, -1, -1, 0, -1, -1>, -1, -1, false>, Eigen::Matrix, -1, -1, 0, -1, -1>}]' 23 | is_any_var_matrix::value, D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>, -1, -1, false>; Mat2 = Eigen::Matrix, -1, -1>; stan::require_all_matrix_t* = 0; stan::require_any_rev_matrix_t* = 0]' 31 | using ret_type = return_var_matrix_t; stanExports_stanmarg.h:4497:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T1__ = Eigen::Matrix; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&)::::, const Eigen::ArrayWrapper, -1, 1> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of, -1, 1> > >(Eigen::ArrayWrapper, -1, 1> >&&):: [with auto:11 = Eigen::ArrayWrapper, -1, 1> >]' 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:58:64: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar, 0, Eigen::Stride<0, 0> > >(Eigen::Map, 0, Eigen::Stride<0, 0> >&&):: [with auto:13 = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:60:68: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/inv.hpp:55:54: required from 'stan::math::inv, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: [with auto:220 = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >]' 55 | x, [](const auto& v) { return v.array().inverse(); }); | ~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:76:68: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 76 | = to_ref_if::value>(inv(sigma_val)); | ~~~^~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::Array, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:40: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); | ~~~~~~~^~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, const Eigen::Array >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:50: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 77 | const auto& y_scaled = to_ref((y_val - mu_val) * inv_sigma); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::Array, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:79:62: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 79 | = to_ref_if::value>(y_scaled * y_scaled); | ~~~~~~~~~^~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from 'stan::math::log, 0, Eigen::Stride<0, 0> > > >(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&):: [with auto:169 = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >]' 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:20: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 87 | logp -= sum(log(sigma_val)) * N / math::size(sigma); | ~~~^~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Array >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:35: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 96 | partials<0>(ops_partials) = -scaled_diff; | ^~~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:45: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; | ~~~~~~~~~~^~~~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::Array >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:59: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >]' 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:94:23: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 94 | logp = -sum(lgamma(alpha_val)) * N / math::size(alpha); | ~~~~~~^~~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:100:27: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 100 | logp += sum(alpha_val * log_beta) * N / max_size(alpha, beta); | ~~~~~~~~~~^~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:44: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 102 | partials<1>(ops_partials) = log_beta + log_y - digamma(alpha_val); | ~~~~~~~~~^~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >]' 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:61: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 102 | partials<1>(ops_partials) = log_beta + log_y - digamma(alpha_val); | ~~~~~~~^~~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:102:52: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 102 | partials<1>(ops_partials) = log_beta + log_y - digamma(alpha_val); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:28: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:35: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:26: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~~~~~~~^~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:44: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~^~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~^~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:43: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val; | ~~~~~~~~~~^~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val; | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, void>::apply(const Eigen::Array&)::, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, void>::apply(const Eigen::Array&)::, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, void>::apply(const Eigen::Array&)::, const Eigen::Array, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, void>::apply(const Eigen::Array&)::, const Eigen::Array >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::log1m_fun; T = Eigen::Array]' 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:79:37: required from 'stan::return_type_t stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_scale_succ = std::vector; T_scale_fail = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 79 | const auto& log1m_y = to_ref(log1m(y_val)); | ~~~~~^~~~~~~ stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14695 | lp_accum__.add((stan::math::beta_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:99:61: required from 'stan::return_type_t stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_scale_succ = std::vector; T_scale_fail = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 99 | = (alpha_val - 1) / y_val + (beta_val - 1) / (y_val - 1); | ~~~~~~~^~~~ stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14695 | lp_accum__.add((stan::math::beta_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:99:52: required from 'stan::return_type_t stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_scale_succ = std::vector; T_scale_fail = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 99 | = (alpha_val - 1) / y_val + (beta_val - 1) / (y_val - 1); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~ stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14695 | lp_accum__.add((stan::math::beta_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:99:35: required from 'stan::return_type_t stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_scale_succ = std::vector; T_scale_fail = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 99 | = (alpha_val - 1) / y_val + (beta_val - 1) / (y_val - 1); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14695 | lp_accum__.add((stan::math::beta_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:105:23: required from 'stan::return_type_t stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_scale_succ = std::vector; T_scale_fail = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 105 | alpha_val + beta_val); | ~~~~~~~~~~^~~~~~~~~~ stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14695 | lp_accum__.add((stan::math::beta_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::lgamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >]' 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:106:23: required from 'stan::return_type_t stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_scale_succ = std::vector; T_scale_fail = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 106 | logp += sum(lgamma(alpha_beta)) * N / max_size(alpha, beta); | ~~~~~~^~~~~~~~~~~~ stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14695 | lp_accum__.add((stan::math::beta_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_scalar_unary.hpp:62:23: required from 'static auto stan::math::apply_scalar_unary::type>::value, void>::type>::apply(const T&) [with F = stan::math::digamma_fun; T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >]' 62 | return x.unaryExpr([](auto&& x) { | ~~~~~~~~~~~^~~~~~~~~~~~~~~ 63 | return apply_scalar_unary>::apply(x); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 64 | }); | ~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:110:64: required from 'stan::return_type_t stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_scale_succ = std::vector; T_scale_fail = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 110 | && !is_constant_all::value > (digamma(alpha_beta)); | ~~~~~~~^~~~~~~~~~~~ stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14695 | lp_accum__.add((stan::math::beta_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:113:21: required from 'stan::return_type_t stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_scale_succ = std::vector; T_scale_fail = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 113 | = log_y + digamma_alpha_beta - digamma(alpha_val); | ~~~~~~^~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14695 | lp_accum__.add((stan::math::beta_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >, const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >, const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >, const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >, const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, void>::apply(const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >&)::, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >, const Eigen::CwiseUnaryOp, 0, Eigen::Stride<0, 0> > >, void>::apply(const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/beta_lpdf.hpp:113:42: required from 'stan::return_type_t stan::math::beta_lpdf(const T_y&, const T_scale_succ&, const T_scale_fail&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_scale_succ = std::vector; T_scale_fail = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 113 | = log_y + digamma_alpha_beta - digamma(alpha_val); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14695:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14695 | lp_accum__.add((stan::math::beta_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map, 0, Eigen::OuterStride<> >' 94 | template class Map | ^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:887:41: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::OuterStride<> >; stan::require_matrix_t* = 0]' 41 | const auto& y_ref = to_ref(y); | ~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:32:18: required from 'Eigen::Matrix::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Diagonal, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Diagonal, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Diagonal, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Diagonal, 0>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Diagonal, 0> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:463:34: required from 'typename MatrixType::RealScalar Eigen::ColPivHouseholderQR::logAbsDeterminant() const [with _MatrixType = Eigen::Matrix; typename MatrixType::RealScalar = double]' 463 | return m_qr.diagonal().cwiseAbs().array().log().sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:51: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Diagonal, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Diagonal, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Diagonal, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, const Eigen::Diagonal, 0> > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:463:42: required from 'typename MatrixType::RealScalar Eigen::ColPivHouseholderQR::logAbsDeterminant() const [with _MatrixType = Eigen::Matrix; typename MatrixType::RealScalar = double]' 463 | return m_qr.diagonal().cwiseAbs().array().log().sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:51: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, const Eigen::Diagonal, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, const Eigen::Diagonal, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, const Eigen::Diagonal, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, const Eigen::Diagonal, 0> > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, const Eigen::Diagonal, 0> > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:463:48: required from 'typename MatrixType::RealScalar Eigen::ColPivHouseholderQR::logAbsDeterminant() const [with _MatrixType = Eigen::Matrix; typename MatrixType::RealScalar = double]' 463 | return m_qr.diagonal().cwiseAbs().array().log().sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:51: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1>, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1>, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1>, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl, 1>, Eigen::Matrix, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve, 1>, Eigen::Matrix >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_left_spd.hpp:46:19: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_left_spd(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_var* = 0; typename stan::return_type::type = double]' 46 | return llt.solve( | ~~~~~~~~~^ 47 | Eigen::Matrix, EigMat2::RowsAtCompileTime, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 48 | EigMat2::ColsAtCompileTime>(b)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:4445:0: required from 'Eigen::Matrix::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T4__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Block, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/add.hpp:45:13: required from 'auto stan::math::add(const Mat1&, const Mat2&) [with Mat1 = Eigen::Block, -1, -1, false>; Mat2 = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0>; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 45 | return m1 + m2; | ~~~^~~~ stanExports_stanmarg.h:4501:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Block, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>, -1, -1, false>; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >; stan::require_all_eigen_t* = 0; stan::require_all_not_st_var* = 0]' 28 | return m1.cwiseProduct(m2); | ~~~~~~~~~~~~~~~^~~~ stanExports_stanmarg.h:4497:0: required from 'stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Block, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1, false> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> >, Eigen::Transpose, -1, -1, false> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >, Eigen::Transpose, -1, -1, false> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >, Eigen::Transpose, -1, -1, false> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1, false> >, Eigen::Transpose, -1, -1, false> > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1, false> >, Eigen::Transpose, -1, -1, false> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase&>(Eigen::Matrix&, const char*, const index_multi&, index_uni)::::, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase&>(Eigen::Matrix&, const char*, const index_multi&, index_uni)::::, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase&>(Eigen::Matrix&, const char*, const index_multi&, index_uni)::::, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&, index_uni)::::, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:470:0: required from 'stan::model::rvalue&>(Eigen::Matrix&, const char*, const index_multi&, index_uni):: [with auto:770 = Eigen::Matrix]' 469 | return Eigen::Matrix, 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/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::model::rvalue&>(Eigen::Matrix&, const char*, const index_multi&, index_uni)::; Args = {Eigen::Matrix&}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/rvalue.hpp:467:0: required from 'Eigen::Matrix::type, -1, 1> stan::model::rvalue(EigMat&&, const char*, const index_multi&, index_uni) [with EigMat = Eigen::Matrix&; stan::require_eigen_dense_dynamic_t* = 0; typename stan::value_type::type = double]' 467 | return stan::math::make_holder( 468 | [name, &row_idx, col_idx](auto& x_ref) { 469 | return Eigen::Matrix, 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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Transpose > > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Transpose > > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Transpose > > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Transpose > > >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Transpose > > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0>, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0>, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0>, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0>, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0>, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Matrix]' 32 | auto too_small = A.ldlt().vectorD().tail(1)(0); | ~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:73:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18267 | stan::math::wishart_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper, 0> >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0> > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from 'stan::math::log, 0> > >(const Eigen::ArrayWrapper, 0> >&):: [with auto:169 = Eigen::ArrayWrapper, 0> >]' 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant_ldlt.hpp:22:17: required from 'stan::value_type_t stan::math::log_determinant_ldlt(LDLT_factor&) [with T = Eigen::Matrix; stan::require_not_rev_matrix_t* = 0; stan::value_type_t = double]' 22 | return sum(log(A.ldlt().vectorD().array())); | ~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:88:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18267 | stan::math::wishart_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:24: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:268:7: required from 'Eigen::MapBase::ScalarWithConstIfNotLvalue& Eigen::MapBase::coeffRef(Eigen::Index) [with Derived = Eigen::Block, -1, 1, true>; ScalarWithConstIfNotLvalue = double; Eigen::Index = long long int]' 15 | EIGEN_STATIC_ASSERT((int(internal::evaluator::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \ | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:367:25: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 367 | matA.col(i).coeffRef(i+1) = 1; | ~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:475:5: required from 'void Eigen::internal::apply_rotation_in_the_plane(Eigen::DenseBase&, Eigen::DenseBase&, const Eigen::JacobiRotation&) [with VectorX = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; VectorY = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; OtherScalar = double]' 475 | EIGEN_PLAIN_ENUM_MIN(evaluator::Alignment, evaluator::Alignment), | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Jacobi/Jacobi.h:315:40: required from 'void Eigen::MatrixBase::applyOnTheRight(Eigen::Index, Eigen::Index, const Eigen::JacobiRotation&) [with OtherScalar = double; Derived = Eigen::Map, 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/4.5/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/4.5/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; DiagType = Eigen::Matrix; SubDiagType = Eigen::Matrix; Eigen::Index = long long int]' 548 | internal::tridiagonal_qr_step(diag.data(), subdiag.data(), start, end, computeEigenvectors ? eivec.data() : (Scalar*)0, n); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:460:49: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 460 | m_info = internal::computeFromTridiagonal_impl(diag, m_subdiag, m_maxIterations, computeEigenvectors, m_eivec); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:221:22: required from 'static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; 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/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, 1, -1, false>, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, 1, -1, false>, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, 1, -1, false>, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 1, -1, false>, 1, -1, false>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false>, 1, -1, false> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:221:22: required from 'static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; 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/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1384:41: required from 'struct Eigen::internal::evaluator_wrapper_base, -1, 1, true>, -1, 1, false> > >' 1384 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8: required from 'struct Eigen::internal::unary_evaluator, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>' 1464 | struct unary_evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::ArrayWrapper, -1, 1, true>, -1, 1, false> >, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 379 | ret = ret && (mat.col(j).tail(size-j-1).array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1384:41: required from 'struct Eigen::internal::evaluator_wrapper_base, -1, 1, false> > >' 1384 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1464:8: required from 'struct Eigen::internal::unary_evaluator, -1, 1, false> >, Eigen::internal::IndexBased, double>' 1464 | struct unary_evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, 1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, false> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::ArrayWrapper, -1, 1, false> >, const Eigen::CwiseNullaryOp, Eigen::Array > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 387 | ret = ret && (A21.array()==Scalar(0)).all(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Array.h:45:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase >, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase >, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase >, -1, 1, false> >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Array, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Array >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >&; stan::require_eigen_t* = 0; stan::require_eigen_vector_t* = 0; stan::require_vt_same* = 0]' 44 | acc.tail(pull) = 1.0 - temp.square(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, const Eigen::Array >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:38:28: required from 'struct Eigen::internal::traits, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >' 38 | >::type Scalar; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >&; stan::require_eigen_t* = 0; stan::require_eigen_vector_t* = 0; stan::require_vt_same* = 0]' 44 | acc.tail(pull) = 1.0 - temp.square(); | ~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >&; stan::require_eigen_t* = 0; stan::require_eigen_vector_t* = 0; stan::require_vt_same* = 0]' 49 | temp /= sqrt(acc.tail(pull) / acc(i)); | ~~~~~~~~~~~~~~~^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/sqrt.hpp:58:51: required from 'stan::math::sqrt, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array > > >(const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array > >&):: [with auto:218 = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Array > >]' 58 | x, [](const auto& v) { return v.array().sqrt(); }); | ~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >&; stan::require_eigen_t* = 0; stan::require_eigen_vector_t* = 0; stan::require_vt_same* = 0]' 53 | CPCs = 0.5 * ((1.0 + CPCs) / (1.0 - CPCs)).log(); // now unbounded | ~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >&; stan::require_eigen_t* = 0; stan::require_eigen_vector_t* = 0; stan::require_vt_same* = 0]' 53 | CPCs = 0.5 * ((1.0 + CPCs) / (1.0 - CPCs)).log(); // now unbounded | ~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >&; stan::require_eigen_t* = 0; stan::require_eigen_vector_t* = 0; stan::require_vt_same* = 0]' 53 | CPCs = 0.5 * ((1.0 + CPCs) / (1.0 - CPCs)).log(); // now unbounded | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >&; stan::require_eigen_t* = 0; stan::require_eigen_vector_t* = 0; stan::require_vt_same* = 0]' 53 | CPCs = 0.5 * ((1.0 + CPCs) / (1.0 - CPCs)).log(); // now unbounded | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >&; stan::require_eigen_t* = 0; stan::require_eigen_vector_t* = 0; stan::require_vt_same* = 0]' 53 | CPCs = 0.5 * ((1.0 + CPCs) / (1.0 - CPCs)).log(); // now unbounded | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, false>, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:40: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper >, const Eigen::ArrayWrapper > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:77:50: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:94:50: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]' 94 | >= 2>(inv_sigma * y_scaled); | ~~~~~~~~~~^~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::Array > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:96:35: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]' 96 | partials<0>(ops_partials) = -scaled_diff; | ^~~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:45: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]' 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; | ~~~~~~~~~~^~~~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:99:59: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]' 99 | partials<2>(ops_partials) = inv_sigma * y_scaled_sq - inv_sigma; | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::ArrayWrapper >, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper > >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log.hpp:66:50: required from 'stan::math::log > >(const Eigen::ArrayWrapper >&):: [with auto:169 = Eigen::ArrayWrapper >]' 66 | x, [](const auto& v) { return v.array().log(); }); | ~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:26: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]' 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~~~~~~~^~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:49: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]' 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~^~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::ArrayWrapper > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:113:57: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]' 113 | partials<0>(ops_partials) = (alpha_val - 1) / y_val - beta_val; | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, const Eigen::ArrayWrapper > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:116:54: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]' 116 | partials<2>(ops_partials) = alpha_val / beta_val - y_val; | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/as_array_or_scalar.hpp:57:50: required from 'stan::math::as_array_or_scalar, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >&>(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >&):: [with auto:13 = const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >]' 57 | return make_holder([](auto& x) { return x.array(); }, std::forward(v)); | ~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::as_array_or_scalar, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >&>(const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >&)::; Args = {const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::MatrixWrapper, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper > > > >&}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14695 | lp_accum__.add((stan::math::beta_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::Matrix; bool NeedToTranspose = false; ResScalar = double]' 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Matrix; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; 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/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector, -1, -1>, std::allocator, -1, -1> > >; bool Jacobian = true; LP = stan::math::var_value; Sizes = {int}; stan::require_std_vector_t* = 0; T = stan::math::var_value; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, Jacobian>( 980 | lp, sizes...)); stanExports_stanmarg.h:12986:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12984 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix< 12985 | std::vector>, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; stan::require_rev_matrix_t* = 0]' 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector, -1, -1>, std::allocator, -1, -1> > >; bool Jacobian = true; LP = stan::math::var_value; Sizes = {int}; stan::require_std_vector_t* = 0; T = stan::math::var_value; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, Jacobian>( 980 | lp, sizes...)); stanExports_stanmarg.h:12986:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12984 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix< 12985 | std::vector>, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector, -1, -1>, std::allocator, -1, -1> > >; bool Jacobian = true; LP = stan::math::var_value; Sizes = {int}; stan::require_std_vector_t* = 0; T = stan::math::var_value; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, Jacobian>( 980 | lp, sizes...)); stanExports_stanmarg.h:12986:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12984 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix< 12985 | std::vector>, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:510:28: required from 'typename Eigen::internal::traits::Scalar Eigen::MatrixBase::trace() const [with Derived = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]' 510 | return derived().diagonal().sum(); | ~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/trace.hpp:26:0: required from 'auto stan::math::trace(const T&) [with T = Eigen::Matrix, -1, -1>; stan::require_rev_matrix_t* = 0]' 26 | return make_callback_var(arena_m.val_op().trace(), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::CwiseBinaryOp, var_value >, const Eigen::Matrix, -1, 1>, const Eigen::Matrix, -1, 1> >; stan::require_all_matrix_t* = 0; stan::require_any_st_var* = 0; var = var_value]' 41 | auto AsolveB = to_arena(A.ldlt().solve(arena_B.val())); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::CwiseBinaryOp, var_value >, const Eigen::Matrix, -1, 1>, const Eigen::Matrix, -1, 1> >; stan::require_all_matrix_t* = 0; stan::require_any_st_var* = 0; var = var_value]' 43 | var res = (arena_B.val_op().transpose() * AsolveB).trace(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 6>' 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::CwiseBinaryOp, var_value >, const Eigen::Matrix, -1, 1>, const Eigen::Matrix, -1, 1> >; stan::require_all_matrix_t* = 0; stan::require_any_st_var* = 0; var = var_value]' 46 | arena_A.adj() += -res.adj() * AsolveB * AsolveB.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::CwiseBinaryOp, var_value >, const Eigen::Matrix, -1, 1>, const Eigen::Matrix, -1, 1> >; stan::require_all_matrix_t* = 0; stan::require_any_st_var* = 0; var = var_value]' 55 | auto AsolveB = to_arena(A.ldlt().solve(value_of(B_ref))); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::CwiseBinaryOp, var_value >, const Eigen::Matrix, -1, 1>, const Eigen::Matrix, -1, 1> >; stan::require_all_matrix_t* = 0; stan::require_any_st_var* = 0; var = var_value]' 57 | var res = (value_of(B_ref).transpose() * AsolveB).trace(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 6>' 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1>&>(const Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of_rec.hpp:110:27: required from 'stan::math::value_of_rec, -1, -1>&>(const Eigen::Matrix, -1, -1>&):: [with auto:1 = const Eigen::Matrix, -1, -1>]' 110 | return m.unaryExpr([](auto x) { return value_of_rec(x); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/lkj_corr_lpdf.hpp:55:20: required from 'stan::return_type_t stan::math::lkj_corr_lpdf(const T_y&, const T_shape&) [with bool propto = false; T_y = Eigen::Matrix, -1, -1>; T_shape = int; stan::return_type_t = var_value]' 55 | check_corr_matrix(function, "Correlation matrix", y_ref); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14715:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14715 | lp_accum__.add(stan::math::lkj_corr_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/accumulator.hpp:135:0: required from 'stan::math::var stan::math::accumulator::type>::value, void>::type>::sum() const [with T = stan::math::var_value; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = stan::math::var_value; stan::math::var = stan::math::var_value]' 135 | inline var sum() const { return stan::math::sum(buf_); } stanExports_stanmarg.h:14942:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14942 | return lp_accum__.sum(); stanExports_stanmarg.h:22491:0: required from 'T_ model_stanmarg_namespace::model_stanmarg::log_prob(std::vector&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:24: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::VectorBlock, -1>; T_covar = Eigen::Block, -1, -1, false>; stan::return_type_t = 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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 4849 | stan::math::multi_normal_lpdf( 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, Eigen::Matrix, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, Eigen::Matrix >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_left_ldlt.hpp:37:24: required from 'Eigen::Matrix::type, -1, EigMat::ColsAtCompileTime> stan::math::mdivide_left_ldlt(LDLT_factor&, const EigMat&) [with T = Eigen::Matrix; EigMat = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0; stan::require_any_not_t::type>, stan::is_fvar::type, void> >* = 0; typename stan::return_type::type = double]' 37 | return A.ldlt().solve( | ~~~~~~~~~~~~~~^ 38 | Eigen::Matrix, EigMat::RowsAtCompileTime, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 39 | EigMat::ColsAtCompileTime>(b)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]' 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:116:13: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]' 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]' 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 33 | return result.setZero().template selfadjointView().rankUpdate( | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^ 34 | M_ref); | ~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Matrix >; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:453:45: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 453 | RealScalar scale = mat.cwiseAbs().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true>, -1, 1, false>, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, true>, -1, 1, false>, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, false>, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:93:22: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:372:86: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false>, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false>, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, false>, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1> >(const char*, const char*, const Eigen::Matrix, -1, 1>&)::; T = Eigen::Matrix, -1, 1>; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>]' 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:42:17: required from 'Eigen::Matrix::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix, -1, -1>; typename stan::value_type::type = var_value]' 42 | check_positive("inverse_spd", "matrix not positive definite", diag_ldlt); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14139:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/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, -1, 1> >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, Eigen::Map, 0, Eigen::Stride<0, 0> > >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:634:22: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:88:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 88 | lp -= 0.5 * nu_ref * log_determinant_ldlt(ldlt_S); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1> >(const char*, const char*, const Eigen::Matrix, -1, 1>&)::; T = Eigen::Matrix, -1, 1>; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>]' 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:71:17: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 71 | check_finite(function, "Location parameter", mu_vec[i]); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/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, -1, 1> >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1> >(const char*, const char*, const Eigen::Matrix, -1, 1>&)::; T = Eigen::Matrix, -1, 1>; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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, -1, 1>]' 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:72:18: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 72 | check_not_nan(function, "Random variable", y_vec[i]); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14424:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/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, -1, 1> >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:510:28: required from 'typename Eigen::internal::traits::Scalar Eigen::MatrixBase::trace() const [with Derived = Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; typename Eigen::internal::traits::Scalar = double]' 510 | return derived().diagonal().sum(); | ~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::CwiseBinaryOp, var_value >, const Eigen::Matrix, -1, 1>, const Eigen::Matrix, -1, 1> >; stan::require_all_matrix_t* = 0; stan::require_any_st_var* = 0; var = var_value]' 43 | var res = (arena_B.val_op().transpose() * AsolveB).trace(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:510:28: required from 'typename Eigen::internal::traits::Scalar Eigen::MatrixBase::trace() const [with Derived = Eigen::Product, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>; typename Eigen::internal::traits::Scalar = double]' 510 | return derived().diagonal().sum(); | ~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::CwiseBinaryOp, var_value >, const Eigen::Matrix, -1, 1>, const Eigen::Matrix, -1, 1> >; stan::require_all_matrix_t* = 0; stan::require_any_st_var* = 0; var = var_value]' 57 | var res = (value_of(B_ref).transpose() * AsolveB).trace(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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]' 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:16: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 62 | check_not_nan(function, "Random variable", y_val); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/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 >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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]' 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:63:15: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 63 | check_finite(function, "Location parameter", mu_val); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/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 >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> > > >(const char*, const char*, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::; T = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> > >]' 29 | elementwise_check([](double x) { return x > 0; }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | "positive"); | ~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:64:17: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 64 | check_positive(function, "Scale parameter", sigma_val); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/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, 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1> >; Matrix2 = stan::math::arena_matrix >; stan::require_rev_matrix_t* = 0; stan::require_st_arithmetic* = 0; stan::math::var = stan::math::var_value]' 67 | x.adj().array() += z.adj() * y.array(); D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:105:28: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 105 | return ops_partials.build(logp); | ~~~~~~~~~~~~~~~~~~^~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1> >; Matrix2 = stan::math::arena_matrix >; stan::require_rev_matrix_t* = 0; stan::require_st_arithmetic* = 0; stan::math::var = stan::math::var_value]' 67 | x.adj().array() += z.adj() * y.array(); D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:105:28: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 105 | return ops_partials.build(logp); | ~~~~~~~~~~~~~~~~~~^~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >(const char*, const char*, const Eigen::Array&)::; T = Eigen::Array; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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]' 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 71 | check_positive_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/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 >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> > > >(const char*, const char*, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >&)::; T = Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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, 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/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:72:24: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 72 | check_positive_finite(function, "Shape parameter", alpha_val); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/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, 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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'struct Eigen::internal::gemm_pack_rhs, 4, 1, false, false>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:91:77: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [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 pack_rhs; | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]' 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]' 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 33 | return result.setZero().template selfadjointView().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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2504:50: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 2504 | typedef typename unpacket_traits::half HalfPacket; | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 2505 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 2508 | HalfPacketSize = unpacket_traits::size, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 2509 | QuarterPacketSize = unpacket_traits::size}; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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, -1> >(const char*, const char*, const Eigen::VectorBlock, -1>&)::; T = Eigen::VectorBlock, -1>; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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, -1>]' 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:71:17: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::VectorBlock, -1>; T_covar = Eigen::Block, -1, -1, false>; stan::return_type_t = double]' 71 | check_finite(function, "Location parameter", mu_vec[i]); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:4849:0: required from 'Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 4849 | stan::math::multi_normal_lpdf( 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, false> >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1> >(const char*, const char*, const Eigen::VectorBlock, -1>&)::; T = Eigen::VectorBlock, -1>; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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, -1>]' 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:72:18: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::VectorBlock, -1>; T_covar = Eigen::Block, -1, -1, false>; stan::return_type_t = double]' 72 | check_not_nan(function, "Random variable", y_vec[i]); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:4849:0: required from 'Eigen::Matrix::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 4849 | stan::math::multi_normal_lpdf( 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, false> >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0>, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:142:7: required from 'Eigen::DenseCoeffsBase::CoeffReturnType Eigen::DenseCoeffsBase::coeff(Eigen::Index) const [with Derived = Eigen::Block, 0>, -1, 1, false>; CoeffReturnType = double; Eigen::Index = long long int]' 142 | EIGEN_STATIC_ASSERT(internal::evaluator::Flags & LinearAccessBit, | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:182:19: required from 'Eigen::DenseCoeffsBase::CoeffReturnType Eigen::DenseCoeffsBase::operator()(Eigen::Index) const [with Derived = Eigen::Block, 0>, -1, 1, false>; CoeffReturnType = double; Eigen::Index = long long int]' 182 | return coeff(index); | ~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with T = Eigen::Matrix]' 32 | auto too_small = A.ldlt().vectorD().tail(1)(0); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:73:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18267 | stan::math::wishart_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::Matrix >, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Matrix >, 1, -1, false> >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:114:1: required from 'ResultType Eigen::internal::member_sum::operator()(const XprType&) const [with XprType = Eigen::Block, const Eigen::Matrix >, 1, -1, false>; ResultType = double; Scalar = double]' 97 | { return mat.MEMBER(); } \ | ~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:21: required from 'const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 1; Scalar = double; Eigen::Index = long long int]' 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 1> >; Scalar = double]' 268 | res = func(res,eval.coeff(index)); | ~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 1>; typename Eigen::internal::traits::Scalar = double]' 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block >, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block >, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block >, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Block >, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Block >, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Block >, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense >, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval >, -1, 1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl, const Eigen::Block >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, true>, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, true>, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, true>, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 1, -1, true>, Eigen::Transpose >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 1, -1, true>, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 1, -1, true>, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, 1, -1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl, 1, -1, true>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:78:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense >, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 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/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 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/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from 'struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >' 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>' 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; 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/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>' 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Block, 1, -1, false>, 1, -1, false> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, 1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:125: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; 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/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0>, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0>, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator, const Eigen::Block, 0>, -1, 1, false> >, Eigen::internal::IndexBased, double>' 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, const Eigen::Block, 0>, -1, 1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from 'class Eigen::internal::visitor_evaluator, const Eigen::Block, 0>, -1, 1, false> > >' 79 | CoeffReadCost = internal::evaluator::CoeffReadCost | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from 'void Eigen::DenseBase::visit(Visitor&) const [with Visitor = Eigen::internal::max_coeff_visitor, const Eigen::Block, 0>, -1, 1, false> >, 0>; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, 0>, -1, 1, false> >]' 123 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Visitor.h:374:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 325 | mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_eigen_matrix_dynamic_t* = 0; stan::require_not_st_autodiff* = 0; matrix_d = Eigen::Matrix]' 35 | LLt(m, m) = Lt.col(m).head(k).squaredNorm(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:43: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t&) [with T_CPCs = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int; stan::value_type_t = double]' 61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; Functor = mul_assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; Functor = Eigen::internal::mul_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; Func = mul_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; Func = mul_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:207:18: required from 'Derived& Eigen::ArrayBase::operator*=(const Eigen::ArrayBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Array >, const Eigen::CwiseUnaryOp, const Eigen::Array > >; Derived = Eigen::Block, -1, 1, false>]' 207 | call_assignment(derived(), other.derived(), internal::mul_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:69:20: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_L(const T&, size_t) [with T = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int]' 69 | acc.tail(pull) *= T_scalar(1.0) - temp.square(); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:32:55: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t) [with T_CPCs = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int]' 32 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K)); | ~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:45:26: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int]' 45 | return read_corr_matrix(corr_constrain(x), k); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:949:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 949 | return corr_matrix_constrain( 950 | this->read>((k * (k - 1)) / 2), 951 | k); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, const Eigen::Block > >, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, const Eigen::Block > >, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, const Eigen::Block > >, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, const Eigen::Block > >, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, const Eigen::Block > >, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, const Eigen::Block > >, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > >, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase > >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense > >, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator > >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator > >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval > >, -1, 1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl >, const Eigen::Block > >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Transpose > >; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Transpose > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 1, -1, true>, Eigen::Transpose > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 1, -1, true>, Eigen::Transpose > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 1, -1, true>, Eigen::Transpose > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, 1, -1, true>, Eigen::Transpose > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, 1, -1, true>, Eigen::Transpose > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, 1, -1, true>, Eigen::Transpose > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense >, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval >, 1, -1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl >, 1, -1, true>, Eigen::Transpose > >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Transpose > >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Transpose > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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 >]' 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:62:16: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]' 62 | check_not_nan(function, "Random variable", y_val); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/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 > >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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 >]' 29 | elementwise_check([](double x) { return std::isfinite(x); }, function, name, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 30 | y, "finite"); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:63:15: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_loc = Eigen::Matrix; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]' 63 | check_finite(function, "Location parameter", mu_val); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/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 > >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 > >(const char*, const char*, const Eigen::ArrayWrapper >&)::; T = Eigen::ArrayWrapper >; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)((Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit) || T::IsVectorAtCompileTime))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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 >]' 24 | elementwise_check([](double x) { return x > 0 && std::isfinite(x); }, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 25 | function, name, y, "positive finite"); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:71:24: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]' 71 | check_positive_finite(function, "Random variable", y_val); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/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 > >::Index' {aka 'long long int'} [-Wsign-compare] 153 | for (size_t i = 0; i < x.size(); i++) { | ~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Transpose > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:25:0: required from 'void stan::math::internal::quad_form_vari_alloc::compute(const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = stan::math::var_value; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = -1]' 25 | matrix_d M = 0.5 * (Cd + Cd.transpose()); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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, -1, -1>; EigMat2 = Eigen::Matrix, -1, -1>; stan::require_all_eigen_t* = 0; stan::require_any_vt_var* = 0]' 37 | return quad_form(A_ref, B, true); stanExports_stanmarg.h:13579:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1> >(const char*, const char*, const Eigen::Matrix, -1, -1>&)::; T = Eigen::Matrix, -1, -1>; Indexings = {}; stan::require_eigen_t* = 0; std::enable_if_t<((bool)(((!(Eigen::internal::traits<_Rhs>::Flags & Eigen::LinearAccessBit)) && (! T::IsVectorAtCompileTime)) && (!(Eigen::internal::traits<_Rhs>::Flags & Eigen::RowMajorBit))))>* = 0]': D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>]' 28 | elementwise_check([](double x) { return !std::isnan(x); }, function, name, y, | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 29 | "not nan"); | ~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:161:0: required from 'Eigen::Matrix, EigMat1::RowsAtCompileTime, EigMat2::ColsAtCompileTime> stan::math::mdivide_left_spd(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix, -1, -1>; EigMat2 = Eigen::Matrix, -1, -1>; stan::require_all_eigen_matrix_base_vt* = 0]' 161 | check_not_nan(function, "A", A_ref); stanExports_stanmarg.h:4445:0: required from 'Eigen::Matrix::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out", stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Matrix, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Matrix >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:533:30: required from 'void Eigen::PartialPivLU::compute() [with _MatrixType = Eigen::Matrix]' 533 | m_l1_norm = m_lu.cwiseAbs().colwise().sum().maxCoeff(); | ~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:133:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, Eigen::internal::member_sum, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix >, Eigen::internal::member_sum, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix >, Eigen::internal::member_sum, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:56:7: required from 'class Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 0>' 56 | class PartialReduxExpr : public internal::dense_xpr_base< PartialReduxExpr >::type, | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:533:46: required from 'void Eigen::PartialPivLU::compute() [with _MatrixType = Eigen::Matrix]' 533 | m_l1_norm = m_lu.cwiseAbs().colwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:133:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, 0, Eigen::Stride<0, 0> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:478:32: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::mean() const [with Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits::Scalar = double]' 478 | return Scalar(derived().redux(Eigen::internal::scalar_sum_op())) / Scalar(this->size()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mean.hpp:25:73: required from 'stan::math::mean >(const std::vector&):: [with auto:229 = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 25 | [](const auto& a) { return a.mean(); }); | ~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:93:13: required from 'static auto stan::math::apply_vector_unary::type>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::mean >(const std::vector&)::; T = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 93 | return f(x); | ~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/functor/apply_vector_unary.hpp:158:45: required from 'static auto stan::math::apply_vector_unary::type, void>, stan::is_stan_scalar::type> >::value>::value, void>::type>::reduce(const T&, const F&) [with F = stan::math::mean >(const std::vector&)::; T = std::vector]' 158 | return apply_vector_unary::reduce(as_column_vector_or_scalar(x), f); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mean.hpp:24:39: required from 'stan::return_type_t stan::math::mean(const T&) [with T = std::vector; stan::require_container_t* = 0; stan::return_type_t = double]' 24 | return apply_vector_unary::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long long int; DataMapper = Eigen::internal::const_blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = false]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h:106:17: required from 'static void Eigen::internal::general_matrix_matrix_triangular_product::run(Index, Index, const LhsScalar*, Index, const RhsScalar*, Index, ResScalar*, Index, Index, const ResScalar&, Eigen::internal::level3_blocking&) [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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:113:12: required from 'static void Eigen::selfadjoint_product_selector::run(MatrixType&, const OtherType&, const typename MatrixType::Scalar&) [with MatrixType = Eigen::Matrix; OtherType = Eigen::Matrix; int UpLo = 2; typename MatrixType::Scalar = double]' 109 | internal::general_matrix_matrix_triangular_product::IsComplex, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 111 | Scalar, OtherIsRowMajor ? ColMajor : RowMajor, (!OtherBlasTraits::NeedToConjugate) && NumTraits::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointProduct.h:126:62: required from 'Eigen::SelfAdjointView& Eigen::SelfAdjointView::rankUpdate(const Eigen::MatrixBase&, const Scalar&) [with DerivedU = Eigen::Matrix; _MatrixType = Eigen::Matrix; unsigned int UpLo = 2; Scalar = double]' 126 | selfadjoint_product_selector::run(_expression().const_cast_derived(), u.derived(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:33:78: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 33 | return result.setZero().template selfadjointView().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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/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::half>::half QuarterPacket; | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::size, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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::size, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Matrix, const Eigen::Matrix > >, 0> > >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T3__ = Eigen::Block, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Block, 1, -1, false>; Functor = assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; SrcXprType = Eigen::Block, 1, -1, false>; Functor = Eigen::internal::assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, 1, -1, false>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, 1, -1, false>; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from 'void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, 1, -1, false>]' 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: required from 'Derived& Eigen::MatrixBase::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Block, 1, -1, false>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 66 | internal::call_assignment(derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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]' 72 | Eigen::Map(&row[0], draws.cols()) = draws.row(i); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1253:0: required from 'SEXPREC* rstan::stan_fit::standalone_gqs(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1253 | ret = stan::services::standalone_generate(model_, draws, 1254 | Rcpp::as(seed), interrupt, logger, *sample_writer_ptr); stanExports_stanmarg.cc:30:0: required from here 30 | .method("standalone_gqs", &rstan::stan_fit ::standalone_gqs) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 16, Eigen::Stride<0, 0> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 16, Eigen::Stride<0, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 16, Eigen::Stride<0, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 16, Eigen::Stride<0, 0> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from 'void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]' 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 850 | typename plain_matrix_type::type tmp(src); | ^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from 'Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Lhs = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Func = generic_product_impl, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 5>::set]' 280 | func(dst.col(j), rhsEval.coeff(Index(0),j) * actual_lhs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:317:41: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from 'void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]' 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 850 | typename plain_matrix_type::type tmp(src); | ^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from 'Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Transpose >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, -1, 1, true>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, -1, 1, true>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, -1, 1, true>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, -1, 1, true>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, -1, 1, true>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense >, -1, 1, true>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, true>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, true>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, true>, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 1, -1, true>, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Core:333: D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of 'class Eigen::internal::gemv_traits': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:306:38: required from 'struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>' 306 | typedef typename Traits::LhsPacket LhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]' 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]' 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from 'static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]' 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from 'static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]' 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 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/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of 'class Eigen::internal::gemv_traits': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:310:42: required from 'struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>' 310 | typedef typename HalfTraits::LhsPacket LhsPacketHalf; | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]' 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]' 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from 'static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]' 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from 'static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]' 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 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/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h: In instantiation of 'class Eigen::internal::gemv_traits': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:314:45: required from 'struct Eigen::internal::general_matrix_vector_product, 1, false, double, Eigen::internal::const_blas_data_mapper, false, 0>' 314 | typedef typename QuarterTraits::LhsPacket LhsPacketQuarter; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; typename Dest::Scalar = double]' 346 | general_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 347 | ::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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Scalar = double]' 385 | internal::gemv_dense_selector::HasUsableDirectAccess) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 388 | >::run(actual_lhs, actual_rhs, dst, alpha); | ~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from 'static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>; Scalar = double]' 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from 'static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; Derived = Eigen::internal::generic_product_impl >, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>]' 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 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/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:44:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 44 | PACKET_DECL_COND_PREFIX(_, Lhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:45:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 45 | PACKET_DECL_COND_PREFIX(_, Rhs, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:46:27: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 46 | PACKET_DECL_COND_PREFIX(_, Res, _PacketSize); | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 51 | Vectorizable = unpacket_traits<_LhsPacket>::vectorizable && | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:51:53: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 52 | unpacket_traits<_RhsPacket>::vectorizable && | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:52:38: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:42: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 53 | int(unpacket_traits<_LhsPacket>::size)==int(unpacket_traits<_RhsPacket>::size), | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:53:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 54 | LhsPacketSize = Vectorizable ? unpacket_traits<_LhsPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:54:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 55 | RhsPacketSize = Vectorizable ? unpacket_traits<_RhsPacket>::size : 1, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:55:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 56 | ResPacketSize = Vectorizable ? unpacket_traits<_ResPacket>::size : 1 | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:56:69: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 59 | typedef typename conditional::type LhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:59:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 60 | typedef typename conditional::type RhsPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:60:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] 61 | typedef typename conditional::type ResPacket; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixVector.h:61:73: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::half' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 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/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, true>, -1, 1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, false>; bool NeedToTranspose = false; ResScalar = double]' 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>, -1, 1, false>; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_eigen_matrix_dynamic_t* = 0; stan::require_not_st_autodiff* = 0; matrix_d = Eigen::Matrix]' 37 | LLt(n, m) = LLt(m, n) = Lt.col(m).head(k).dot(Lt.col(n).head(k)); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:43: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t&) [with T_CPCs = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int; stan::value_type_t = double]' 61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Transpose > >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Transpose > >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Transpose > >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::Transpose > >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::Transpose > >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, Eigen::Transpose > >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, -1, 1, true>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > >, -1, 1, true>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, -1, 1, true>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, -1, 1, true>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase > >, -1, 1, true>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense > >, -1, 1, true>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 1, -1, true>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 1, -1, true>, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 1, -1, true>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 1, -1, true>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, 1, -1, true>, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense >, 1, -1, true>, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1, false> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, 1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, -1, -1, false>, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1, false>, const Eigen::Product, const Eigen::Block, -1, 1, false>, const Eigen::Matrix >, Eigen::Transpose, const Eigen::Block, -1, 1, false>, const Eigen::Matrix > >, 0> > >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, 6>' 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:29:8: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1626:36: required from 'struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0> >' 1626 | typedef typename XprType::Scalar Scalar; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:65:8: required from 'struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0> >' 65 | struct evaluator, DiagIndex> > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:126:7: required from 'class Eigen::internal::dense_product_base, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, 6>' 126 | class dense_product_base | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:29:8: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1626:36: required from 'struct Eigen::internal::evaluator, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0> >' 1626 | typedef typename XprType::Scalar Scalar; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:65:8: required from 'struct Eigen::internal::evaluator, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0> >' 65 | struct evaluator, DiagIndex> > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, 1, true>, -1, 1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, 1, true>, -1, 1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:129:38: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true>, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true>, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, 1, true>, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, 1, true>, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, 1, true>, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:129:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:131:25: required from 'void Eigen::MatrixBase::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::VectorBlock, -1, 1, true>, -1>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]' 131 | this->row(0) -= tau * tmp; | ~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:550:35: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:132:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Block, -1, 1, true>, -1, 1, false>; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, -1, 1, true>, -1, 1, false> >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t stan::math::sum(const T&) [with T = Eigen::VectorBlock, -1, 1, true>, -1>; stan::require_eigen_vt* = 0; stan::value_type_t = double]' 47 | return m.sum(); | ~~~~~^~ stanExports_stanmarg.h:4337:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix, const Eigen::Matrix > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; stan::require_eigen_vt* = 0; stan::value_type_t = double]' 47 | return m.sum(); | ~~~~~^~ stanExports_stanmarg.h:3419:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::Matrix >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::Matrix > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:53: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, true>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Functor = assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Functor = Eigen::internal::assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from 'void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CommaInitializer.h:159:10: required from 'Eigen::CommaInitializer Eigen::DenseBase::operator<<(const Eigen::DenseBase&) [with OtherDerived = Eigen::Map, 0, Eigen::Stride<0, 0> >; Derived = Eigen::Matrix]' 159 | return CommaInitializer(*static_cast(this), other); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/append_row.hpp:102:10: required from 'Eigen::Matrix::type, -1, 1> stan::math::append_row(const ColVec&, const Scal&) [with ColVec = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scal = double; stan::require_t >* = 0; stan::require_stan_scalar_t* = 0; typename stan::return_type::type = double]' 102 | result << A.template cast(), B; | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; T_return = double; ArrayAT = Eigen::Array; ArrayBT = Eigen::Array; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 29 | ArrayBT b_array = append_row(as_array_or_scalar(b), 1.0); | ~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Tb = std::vector; Tz = double; stan::require_all_vector_t* = 0; stan::require_stan_scalar_t* = 0]' 123 | return internal::hypergeometric_3F2_infsum(a, b, z); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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* = 0]' 148 | return hypergeometric_3F2(std::vector(a), std::vector(b), z); | ~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, double>' 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 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/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 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/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:221:28: required from 'static typename Eigen::NumTraits::Scalar>::Real Eigen::internal::lpNorm_selector::run(const Eigen::MatrixBase&) [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 221 | return m.cwiseAbs().sum(); | ~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:269:52: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::lpNorm() const [with int p = 1; Derived = Eigen::Block, -1, 1, true>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 269 | return internal::lpNorm_selector::run(*this); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:514:74: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; 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/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Block, 1, -1, false>; Rhs = Eigen::Block, -1, 1, false>]' 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 359 | mat.coeffRef(k,k) -= (A10 * temp.head(k)).value(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase >, -1, 1, false> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase >, -1, 1, false> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase >, -1, 1, false> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, -1, 1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix, const Eigen::Matrix > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::Matrix; bool NeedToTranspose = false; ResScalar = double]' 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Matrix; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:199:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; 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/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense >, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval >, -1, 1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, const Eigen::Block >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]' 47 | return m.sum(); | ~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/accumulator.hpp:73:0: required from 'void stan::math::accumulator::type>::value, void>::type>::add(const S&) [with S = Eigen::CwiseUnaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; stan::require_matrix_t* = 0; T = stan::math::var_value; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = stan::math::var_value]' 73 | buf_.push_back(stan::math::sum(m)); stanExports_stanmarg.h:14316:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Array, const Eigen::Array > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::Array, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]' 47 | return m.sum(); | ~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:82:38: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 82 | T_partials_return logp = -0.5 * sum(y_scaled_sq); | ~~~^~~~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]' 47 | return m.sum(); | ~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/normal_lpdf.hpp:87:16: required from 'stan::return_type_t stan::math::normal_lpdf(const T_y&, const T_loc&, const T_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_loc = Eigen::Matrix, -1, 1>; T_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 87 | logp -= sum(log(sigma_val)) * N / math::size(sigma); | ~~~^~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14607:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14607 | lp_accum__.add(stan::math::normal_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseUnaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > > > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]' 47 | return m.sum(); | ~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:100:16: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 100 | logp += sum(alpha_val * log_beta) * N / max_size(alpha, beta); | ~~~^~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::CwiseNullaryOp, const Eigen::Array > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]' 47 | return m.sum(); | ~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:106:16: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::Array >; stan::require_eigen_vt* = 0; stan::value_type_t = double]' 47 | return m.sum(); | ~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix, -1, 1>; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = var_value]' 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~^~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<-1, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<-1, 0> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<-1, 0> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<-1, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<-1, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<-1, 0> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, -1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, -1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, -1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Ref.h:44:50: required from 'struct Eigen::internal::traits, 0, Eigen::OuterStride<> > >::match, 0, Eigen::OuterStride<> >, -1, -1, false> >' 44 | DerivedAlignment = int(evaluator::Alignment), | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Ref.h:288:101: required by substitution of 'template Eigen::Ref, 0, Eigen::OuterStride<> >::Ref(const Eigen::DenseBase&, typename Eigen::internal::enable_if<(bool)(Eigen::internal::traits, 0, Eigen::OuterStride<> > >::match::MatchAtCompileTime), Derived>::type*) [with Derived = Eigen::Block, 0, Eigen::OuterStride<> >, -1, -1, false>]' 288 | typename internal::enable_if::MatchAtCompileTime),Derived>::type* = 0); | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:463:17: required from 'static Eigen::Index Eigen::internal::partial_lu_impl::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/4.5/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; 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/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:543:31: required from 'void Eigen::PartialPivLU::compute() [with _MatrixType = Eigen::Matrix]' 543 | internal::partial_lu_inplace(m_lu, m_rowsTranspositions, nb_transpositions); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:133:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, Eigen::Ref, 0, Eigen::OuterStride<> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, Eigen::Ref, 0, Eigen::OuterStride<> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, Eigen::Ref, 0, Eigen::OuterStride<> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::OuterStride<> >, Eigen::Ref, 0, Eigen::OuterStride<> >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::OuterStride<> >, Eigen::Ref, 0, Eigen::OuterStride<> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::OuterStride<> >, Eigen::Ref, 0, Eigen::OuterStride<> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:495:30: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:110:23: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1, false>, Eigen::Transpose, 1, -1, false> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:45: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1, false>, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1, false>, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:58: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Transpose, -1, -1, false>, 1, -1, false> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:332:45: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, true>; SrcXprType = Eigen::Matrix; Functor = assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::Matrix; Functor = Eigen::internal::assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, true>; Src = Eigen::Matrix; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, -1, true>; Src = Eigen::Matrix; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T2 = Eigen::Matrix; = void]' 49 | result.leftCols(Acols) = A.template cast(); | ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:2847:0: required from 'Eigen::Matrix::type, typename stan::base_type::type>::type, -1, -1> model_stanmarg_namespace::calc_B_tilde(const T0__&, const T1__&, const std::vector&, const int&, std::ostream*) [with T0__ = Eigen::Matrix; T1__ = Eigen::Matrix; stan::require_all_t, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >, const Eigen::Matrix >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >, const Eigen::Matrix > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:53: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, false> >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::VectorBlock, -1>; T_loc = Eigen::VectorBlock, -1>; T_covar = Eigen::Block, -1, -1, false>; stan::return_type_t = 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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type, -1, 1> model_stanmarg_namespace::calc_log_lik_x(const std::vector >&, const T1__&, const T2__&, const T3__&, const T4__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = Eigen::Matrix; T2__ = Eigen::Matrix; T3__ = Eigen::Matrix; T4__ = Eigen::Matrix; stan::require_all_t, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 4849 | stan::math::multi_normal_lpdf( 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block >, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, true>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, true>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 1, -1, true>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 1, -1, true>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>, 1, -1, true>; U = Eigen::Block >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false> >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false> >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, false> >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1, false>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::Block, -1, 1, true>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, false>; bool NeedToTranspose = false; ResScalar = double]' 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>, -1, 1, false>; Derived = Eigen::Block, -1, 1, false>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:372:86: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false>, 1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::InnerStride<1> >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/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; SrcXprType = Eigen::Block, 0, Eigen::InnerStride<1> >, -1, 1, false>; Functor = assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array; SrcXprType = Eigen::Block, 0, Eigen::InnerStride<1> >, -1, 1, false>; Functor = Eigen::internal::assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Block, 0, Eigen::InnerStride<1> >, -1, 1, false>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Array; Src = Eigen::Block, 0, Eigen::InnerStride<1> >, -1, 1, false>; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from 'void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Array; Src = Eigen::Block, 0, Eigen::InnerStride<1> >, -1, 1, false>]' 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_L.hpp:126:21: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_L(const T&, size_t, stan::value_type_t&) [with T = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int; stan::value_type_t = double]' 126 | return read_corr_L(CPCs_ref, K); | ~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/read_corr_matrix.hpp:61:55: required from 'Eigen::Matrix::type, -1, -1> stan::math::read_corr_matrix(const T_CPCs&, size_t, stan::value_type_t&) [with T_CPCs = Eigen::Matrix; stan::require_eigen_vector_t* = 0; typename stan::value_type::type = double; size_t = long long unsigned int; stan::value_type_t = double]' 61 | return multiply_lower_tri_self_transpose(read_corr_L(CPCs, K, log_prob)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_constrain.hpp:74:26: required from 'Eigen::Matrix::type, -1, -1> stan::math::corr_matrix_constrain(const T&, Eigen::Index, stan::return_type_t&) [with T = Eigen::Map, 0, Eigen::Stride<0, 0> >; stan::require_eigen_col_vector_t* = 0; typename stan::value_type::type = double; Eigen::Index = long long int; stan::return_type_t = double]' 74 | return read_corr_matrix(corr_constrain(x, lp), k, lp); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:945:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, Eigen::Index) [with Ret = Eigen::Matrix; bool Jacobian = false; LP = double; stan::require_not_std_vector_t* = 0; stan::require_matrix_t* = 0; T = double; Eigen::Index = long long int]' 945 | return corr_matrix_constrain( 946 | this->read>((k * (k - 1)) / 2), 947 | k, lp); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector >; bool Jacobian = false; LP = double; Sizes = {int}; stan::require_std_vector_t* = 0; T = double; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, 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>, 15015 | jacobian__>(lp__, Psi_r_mat_1_1dim__, 15016 | Psi_r_mat_1_3dim__); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block > >, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 1, -1, true>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 1, -1, true>, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 1, -1, true>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 1, -1, true>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, 1, -1, true>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >, 1, -1, true>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>, 1, -1, true>; U = Eigen::Block > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/sum.hpp:47:15: required from 'stan::value_type_t stan::math::sum(const T&) [with T = Eigen::CwiseBinaryOp, const Eigen::ArrayWrapper, 0, Eigen::Stride<0, 0> > >, const Eigen::ArrayWrapper > >; stan::require_eigen_vt* = 0; stan::value_type_t = double]' 47 | return m.sum(); | ~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/gamma_lpdf.hpp:109:16: required from 'stan::return_type_t stan::math::gamma_lpdf(const T_y&, const T_shape&, const T_inv_scale&) [with bool propto = false; T_y = Eigen::Matrix; T_shape = std::vector; T_inv_scale = std::vector; stan::require_all_not_nonscalar_prim_or_rev_kernel_expression_t* = 0; stan::return_type_t = double]' 109 | logp -= sum(beta_val * y_val) * N / max_size(beta, y); | ~~~^~~~~~~~~~~~~~~~~~ stanExports_stanmarg.h:14689:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; VecR = std::vector; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = double; std::ostream = std::basic_ostream]' 14689 | lp_accum__.add(stan::math::gamma_lpdf(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&, std::vector&, std::ostream*) const [with bool propto__ = false; bool jacobian__ = false; T_ = double; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/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(cont_vector, disc_vector, 57 | &message); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:502:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Transpose >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:469:72: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product, Eigen::Transpose >, 1> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:469:55: required from 'static void Eigen::internal::generic_product_impl::eval_dynamic_impl(Dst&, const LhsT&, const RhsT&, const Func&, const Scalar&, Eigen::internal::true_type) [with Dst = Eigen::Matrix; LhsT = Eigen::Matrix; RhsT = Eigen::Transpose >; Func = Eigen::internal::assign_op; Scalar = double; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; Rhs = Eigen::Transpose >]' 469 | call_restricted_packet_assignment_no_alias(dst, s * lhs.lazyProduct(rhs), func); | ~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:446:22: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, -1, 1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, -1, 1, false>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, -1, 1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, -1, 1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, -1, 1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense >, -1, 1, false>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:377:43: required from 'static Eigen::Index Eigen::internal::partial_lu_impl::unblocked_lu(MatrixTypeRef&, PivIndex*, PivIndex&) [with Scalar = double; int StorageOrder = 1; PivIndex = int; int SizeAtCompileTime = -1; Eigen::Index = long long int; MatrixTypeRef = Eigen::Ref, 0, Eigen::OuterStride<> >]' 377 | = lu.col(k).tail(rows-k).unaryExpr(Scoring()).maxCoeff(&row_of_biggest_in_col); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:439:26: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:400:114: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::CwiseNullaryOp, Eigen::Matrix >, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::CwiseNullaryOp, Eigen::Matrix >, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::CwiseNullaryOp, Eigen::Matrix >, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::CwiseNullaryOp, Eigen::Matrix >, 2, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::CwiseNullaryOp, Eigen::Matrix >, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::CwiseNullaryOp, Eigen::Matrix >, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Solve >, Eigen::CwiseNullaryOp, Eigen::Matrix > >; _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/4.5/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:44:20: required from 'Eigen::Matrix::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix; typename stan::value_type::type = double]' 44 | return ldlt.solve( | ~~~~~~~~~~^ 45 | Eigen::Matrix::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Matrix, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Matrix, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Matrix, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Matrix, 2, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Matrix, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Matrix, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:610:38: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Solve >, Eigen::CwiseNullaryOp, Eigen::Matrix > >; _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/4.5/StanHeaders/include/stan/math/prim/fun/inverse_spd.hpp:44:20: required from 'Eigen::Matrix::type, -1, -1> stan::math::inverse_spd(const EigMat&) [with EigMat = Eigen::Matrix; typename stan::value_type::type = double]' 44 | return ldlt.solve( | ~~~~~~~~~~^ 45 | Eigen::Matrix::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from 'class Eigen::internal::visitor_evaluator, 1, -1, false> >' 79 | CoeffReadCost = internal::evaluator::CoeffReadCost | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from 'void Eigen::DenseBase::visit(Visitor&) const [with Visitor = Eigen::internal::max_coeff_visitor, 1, -1, false>, 0>; Derived = Eigen::Block, 1, -1, false>]' 123 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Visitor.h:374:14: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff(IndexType*) const [with int NaNPropagation = 0; IndexType = long long int; Derived = Eigen::Block, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]' 374 | this->visit(maxVisitor); | ~~~~~~~~~~~^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:501:37: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff(IndexType*) const [with IndexType = long long int; Derived = Eigen::Block, 1, -1, false>; typename Eigen::internal::traits::Scalar = double]' 501 | return maxCoeff(index); | ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:521:90: required from 'void Eigen::ColPivHouseholderQR::computeInPlace() [with _MatrixType = Eigen::Matrix]' 521 | RealScalar biggest_col_sq_norm = numext::abs2(m_colNormsUpdated.tail(cols-k).maxCoeff(&biggest_col_index)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:477:3: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Block, 1, -1, false>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Block, 1, -1, false> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:328:36: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1, false>, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1, false>, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1, false>, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, const Eigen::Block, -1, -1, false>, 1, -1, false>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, const Eigen::Block, -1, -1, false>, 1, -1, false> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:98:40: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, -1, false>, 1, -1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:328:36: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Block >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Block >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense >, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval >, -1, 1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl, const Eigen::Block >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false>, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false>, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Transpose >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 1, -1, false>, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Matrix, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Matrix, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false> >; Functor = assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false> >; Functor = Eigen::internal::assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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, -1>; T2 = const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false> >&; stan::require_all_eigen_t* = 0]' 92 | x = std::forward(y); D:/RCompile/CRANpkg/lib/4.5/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&; Vec2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, false> >; stan::require_all_vector_t* = 0; stan::require_all_not_std_vector_t* = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:78:71: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 2, Eigen::Stride<0, 0> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 2, Eigen::Stride<0, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 2, Eigen::Stride<0, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 2, Eigen::Stride<0, 0> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, -1, 1, false> >, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:375:18: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 374 | matA.bottomRightCorner(remainingSize, remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 375 | .rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), Scalar(-1)); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator >, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator >, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 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/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 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/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; Dest = Eigen::Block, -1, 1, false>; typename Dest::Scalar = double]' 296 | dest.matrix() += actualAlpha * MappedDest(actualDestPtr, dest.size()); | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false> >' 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; SrcXprType = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Functor = assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array; SrcXprType = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Functor = Eigen::internal::assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/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; SrcXprType = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Functor = assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Array; SrcXprType = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Functor = Eigen::internal::assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Derived = Eigen::Array]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, false>, 1, -1, false>; Derived = Eigen::Array]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Array.h:288:29: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator >, -1, 1, false> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator >, -1, 1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >, -1, 1, false> >; SrcXprType = Eigen::Array; Functor = assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose >, -1, 1, false> >; SrcXprType = Eigen::Array; Functor = Eigen::internal::assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >, -1, 1, false>; Src = Eigen::Array; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; T_CPCs = Eigen::ArrayWrapper >; T_sds = Eigen::Array&; stan::require_eigen_t* = 0; stan::require_all_eigen_vector_t* = 0; stan::require_all_vt_same* = 0]' 51 | factor_U(U, CPCs); | ~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/corr_matrix_free.hpp:45:38: required from 'Eigen::Matrix::type, -1, 1> stan::math::corr_matrix_free(const T&) [with T = Eigen::Matrix; stan::require_eigen_t* = 0; typename stan::value_type::type = double]' 45 | bool successful = factor_cov_matrix(y, x.array(), sds); | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:480:0: required from 'void stan::io::serializer::write_free_corr_matrix(const Mat&) [with Mat = Eigen::Matrix; stan::require_not_std_vector_t* = 0; T = double]' 480 | this->write(stan::math::corr_matrix_free(x)); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/serializer.hpp:492:0: required from 'void stan::io::serializer::write_free_corr_matrix(const StdVec&) [with StdVec = std::vector >; stan::require_std_vector_t* = 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; stan::require_vector_t* = 0; std::ostream = std::basic_ostream]' 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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>; Rhs = Eigen::Transpose >; Dest = Eigen::Block, 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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/BlasUtil.h:506:13: required from 'struct Eigen::internal::blas_traits, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 506 | >::type DirectLinearAccessType; | ^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, const Eigen::Block, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix, 0>, const Eigen::Block, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix, 0>, const Eigen::Block, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::Matrix, 0>, const Eigen::Block, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::Matrix, 0>, const Eigen::Block, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, Eigen::Matrix, 0>, const Eigen::Block, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, -1, 1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl >, Eigen::Matrix, 0>, const Eigen::Block, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Product >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix, 0>, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix, 0>, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense >, Eigen::Matrix, 0>, 1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl >, Eigen::Matrix, 0>, 1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block >, Eigen::Matrix, 0>, 1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, Eigen::Matrix, 0>, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, Eigen::Matrix, 0>, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Product >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Matrix, 0>, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Matrix, 0>, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Matrix, 0>, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense > >, Eigen::Matrix, 0>, 1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl > >, Eigen::Matrix, 0>, 1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block > >, Eigen::Matrix, 0>, 1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator > >, Eigen::Matrix, 0>, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator > >, Eigen::Matrix, 0>, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval > >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl > >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Product > >, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product > >, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, -1, -1, false>, -1, -1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl, -1, 1, true>, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Lhs = Eigen::Transpose, -1, 1, true>, -1, 1, false> >; Rhs = Eigen::Block, -1, -1, false>, -1, -1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, 1, true>, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; Src = Eigen::Product, -1, 1, true>, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/NoAlias.h:43:31: required from 'ExpressionType& Eigen::NoAlias::operator=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, 1, true>, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>; ExpressionType = Eigen::Map, 0, Eigen::Stride<0, 0> >; StorageBase = Eigen::MatrixBase]' 43 | call_assignment_no_alias(m_expression, other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:129:19: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'struct Eigen::internal::gemm_pack_rhs, 4, 1, false, true>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:233:85: required from 'static void Eigen::internal::triangular_solve_matrix::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking&) [with Scalar = double; Index = long long int; int Mode = 2; bool Conjugate = false; int TriStorageOrder = 1; int OtherInnerStride = 1]' 233 | gemm_pack_rhs pack_rhs_panel; | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from 'static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; int Side = 2; int Mode = 2]' 100 | triangular_solve_matrix | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from 'void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 2; OtherDerived = Eigen::Block, -1, -1, false>; _MatrixType = const Eigen::Transpose, -1, -1, false> >; unsigned int _Mode = 2]' 181 | internal::triangular_solver_selector::type, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 182 | Side, Mode>::run(derived().nestedExpression(), otherCopy); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:364:96: required from 'static Eigen::Index Eigen::internal::llt_inplace::blocked(MatrixType&) [with MatrixType = Eigen::Matrix; Scalar = double; Eigen::Index = long long int]' 364 | if(rs>0) A11.adjoint().template triangularView().template solveInPlace(A21); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68: required from 'static bool Eigen::internal::LLT_Traits::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix]' 408 | { return llt_inplace::blocked(m)==-1; } | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:456:42: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2504:50: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 2504 | typedef typename unpacket_traits::half HalfPacket; | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2505:82: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 2505 | typedef typename unpacket_traits::half>::half QuarterPacket; | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2508:56: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 2508 | HalfPacketSize = unpacket_traits::size, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2509:70: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 2509 | QuarterPacketSize = unpacket_traits::size}; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, -1, 1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, -1, 1, false>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, -1, 1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, -1, 1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, -1, 1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense >, -1, 1, false>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, false>, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 1, -1, false>, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1, false> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1, false> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1, false> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> > >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false> > >, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> > >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> > >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false> > >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false> > >, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false> > >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false> > >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, -1, -1, false> > >, -1, 1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl, -1, -1, false> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Transpose, -1, -1, false> > >; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Transpose, -1, -1, false> > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 1, -1, true>, Eigen::Transpose, -1, -1, false> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >, 1, -1, true>, Eigen::Transpose, -1, -1, false> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >, 1, -1, true>, Eigen::Transpose, -1, -1, false> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1, false> >, 1, -1, true>, Eigen::Transpose, -1, -1, false> > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1, false> >, 1, -1, true>, Eigen::Transpose, -1, -1, false> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1, false> >, 1, -1, true>, Eigen::Transpose, -1, -1, false> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false> >, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false> >, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false> >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false> >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, -1, -1, false> >, 1, -1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl, -1, -1, false> >, 1, -1, true>, Eigen::Transpose, -1, -1, false> > >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Transpose, -1, -1, false> > >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Transpose, -1, -1, false> > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, const Eigen::Block > > >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, const Eigen::Block > > >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, const Eigen::Block > > >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, const Eigen::Block > > >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, const Eigen::Block > > >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, const Eigen::Block > > >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > > >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > > >, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > > >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > > >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase > > >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense > > >, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator > > >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator > > >, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval > > >, -1, 1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl > >, const Eigen::Block > > >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose > >; Rhs = Eigen::Transpose > > >; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose > >; Rhs = Eigen::Transpose > > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, 1, -1, false>, Eigen::Transpose > > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, 1, -1, false>, Eigen::Transpose > > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, 1, -1, false>, Eigen::Transpose > > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, 1, -1, false>, Eigen::Transpose > > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, 1, -1, false>, Eigen::Transpose > > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, 1, -1, false>, Eigen::Transpose > > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > >, 1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase > >, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense > >, 1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator > >, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator > >, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval > >, 1, -1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl > >, 1, -1, false>, Eigen::Transpose > > >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose > >; Rhs = Eigen::Transpose > > >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose > >; Rhs = Eigen::Transpose > > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 6 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 2, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_left_ldlt.hpp:37:24: required from 'Eigen::Matrix::type, -1, EigMat::ColsAtCompileTime> stan::math::mdivide_left_ldlt(LDLT_factor&, const EigMat&) [with T = Eigen::Matrix; EigMat = Eigen::Matrix; stan::require_eigen_t* = 0; stan::require_all_not_st_var* = 0; stan::require_any_not_t::type>, stan::is_fvar::type, void> >* = 0; typename stan::return_type::type = double]' 37 | return A.ldlt().solve( | ~~~~~~~~~~~~~~^ 38 | Eigen::Matrix, EigMat::RowsAtCompileTime, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 39 | EigMat::ColsAtCompileTime>(b)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18267 | stan::math::wishart_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, -1, 1, true>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, -1, 1, true>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept_check.hpp:167:5: required from 'struct boost::CopyConstructible<__gnu_cxx::__normal_iterator > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:125:16: required from 'struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >' 125 | struct IncrementableIteratorConcept : CopyConstructible | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >' 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied > > >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/BH/include/boost/concept_check.hpp:31: D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator > >]' 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept_check.hpp:208:5: required from 'struct boost::Convertible' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: required from 'struct boost::concepts::requirement_)>' 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_concepts.hpp:114:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]' 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement::failed() [with Model = boost::Convertible]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_concepts.hpp:114:7: required from 'struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >' 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied > > >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied > > >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::incrementable_traversal_tag]' 37 | ~model() | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:136:13: required from 'struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >' 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied > > >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied > > >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >]' 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept_check.hpp:233:5: required from 'struct boost::EqualityComparable<__gnu_cxx::__normal_iterator > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >' 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied > > >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied > > >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator > >]' 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept_check.hpp:208:5: required from 'struct boost::Convertible' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: required from 'struct boost::concepts::requirement_)>' 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:152:13: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]' 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement::failed() [with Model = boost::Convertible]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:152:13: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied > > >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied > > >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: required from 'struct boost::concepts::requirement_ > >)>' 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:278:9: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::single_pass_traversal_tag]' 37 | ~model() | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:158:13: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied > > >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied > > >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: required from 'struct boost::concepts::requirement_ > >)>' 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:278:9: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]' 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement::failed() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:278:9: required from 'struct boost::SinglePassRangeConcept > > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied > > > >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied > > > >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: required from 'struct boost::concepts::requirement_ > > >)>' 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/algorithm/equal.hpp:174:13: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::range_detail::SinglePassIteratorConcept::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]' 37 | ~model() | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > > >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:284:9: required from 'struct boost::SinglePassRangeConcept > > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied > > > >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied > > > >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: required from 'struct boost::concepts::requirement_ > > >)>' 72 | struct requirement_ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/algorithm/equal.hpp:174:13: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:5: note: in a call to non-static member function 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::SinglePassRangeConcept > > >]' 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ^ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp: In instantiation of 'static void boost::concepts::requirement::failed() [with Model = boost::SinglePassRangeConcept > > >]': D:/RCompile/CRANpkg/lib/4.5/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 > >; SinglePassRange2 = boost::iterator_range<__gnu_cxx::__normal_iterator > >]' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/iterator_range_core.hpp:644:32: required from 'bool boost::operator==(const iterator_range&, const iterator_range&) [with Iterator1T = __gnu_cxx::__normal_iterator >; Iterator2T = __gnu_cxx::__normal_iterator >]' 644 | return boost::equal( l, r ); | ~~~~~~~~~~~~^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/find_iterator.hpp:359:0: required from 'bool boost::algorithm::split_iterator::equal(const boost::algorithm::split_iterator&) const [with IteratorT = __gnu_cxx::__normal_iterator >]' 359 | m_Match==Other.m_Match && D:/RCompile/CRANpkg/lib/4.5/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 > >; Facade2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; mpl_::true_ = mpl_::bool_]' 649 | return f1.equal(f2); | ~~~~~~~~^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:981:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator==(const iterator_facade&, const iterator_facade&) [with Derived1 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; V1 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >; TC1 = forward_traversal_tag; Reference1 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >&; Difference1 = long long int; Derived2 = boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >; V2 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >; TC2 = forward_traversal_tag; Reference2 = const boost::iterator_range<__gnu_cxx::__normal_iterator > >&; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&rhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 969 | , BOOST_ITERATOR_CONVERTIBLE(Derived2,Derived1) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 970 | ); \ | ~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_adaptor.hpp:305:29: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/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/4.5/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::SinglePassRangeConcept::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator > >]' 37 | ~model() | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]' 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]' 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]' 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Functor = assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Functor = Eigen::internal::assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from 'void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, false>, const Eigen::CwiseNullaryOp, const Eigen::Matrix > >]' 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:363:59: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 363 | matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Core:337: D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h: In instantiation of 'static void Eigen::internal::selfadjoint_matrix_vector_product::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: required from 'static void Eigen::internal::selfadjoint_product_impl::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Scalar = double]' 227 | internal::selfadjoint_matrix_vector_product::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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:805:109: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]' 805 | selfadjoint_product_impl::run(dst, lhs.nestedExpression(), rhs, alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from 'static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>; Scalar = double]' 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from 'static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>]' 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:62:121: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 62 | conj_helper::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, IsRowMajor), ConjugateRhs> pcj0; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:62:121: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:63:121: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 63 | conj_helper::IsComplex && EIGEN_LOGICAL_XOR(ConjugateLhs, !IsRowMajor), ConjugateRhs> pcj1; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:63:121: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1, false>, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1, false>, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator > >, -1, 1, true>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator > >, -1, 1, true>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, 1, -1, true>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, 1, -1, true>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator >, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator >, 1, -1, true>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, 1, -1, true>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gemm_pack_rhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long long int; DataMapper = Eigen::internal::blas_data_mapper; int nr = 4; bool Conjugate = false; bool PanelMode = true]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:155:19: required from 'static void Eigen::internal::triangular_solve_matrix::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking&) [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/4.5/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from 'static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Matrix; Rhs = Eigen::Matrix; int Side = 1; int Mode = 1]' 100 | triangular_solve_matrix | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from 'void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 1; OtherDerived = Eigen::Matrix; _MatrixType = const Eigen::Matrix; unsigned int _Mode = 1]' 181 | internal::triangular_solver_selector::type, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 182 | Side, Mode>::run(derived().nestedExpression(), otherCopy); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:522:37: required from 'void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Matrix; _MatrixType = const Eigen::Matrix; unsigned int _Mode = 1]' 522 | { return solveInPlace(other); } | ~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:520:25: required from 'void Eigen::LLT::solveInPlace(const Eigen::MatrixBase&) const [with Derived = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 520 | matrixL().solveInPlace(bAndX); | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 4445 | stan::math::mdivide_left_spd(H, A))), "assigning variable out", stanExports_stanmarg.h:14152:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 2459 | PacketBlock kernel; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:22: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:37: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; int ProductTag = 6; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Map, 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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1632:27: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; int ProductTag = 6; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Map, 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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1632:27: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:22: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:37: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; int ProductTag = 6; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Map, 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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1632:27: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; int ProductTag = 6; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Map, 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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1632:27: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, member_sum, 0>; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 0>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 0> >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 0>; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 0>; typename Eigen::internal::traits::Scalar = double]' 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 0>; typename Eigen::internal::traits::Scalar = double]' 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:533:57: required from 'void Eigen::PartialPivLU::compute() [with _MatrixType = Eigen::Matrix]' 533 | m_l1_norm = m_lu.cwiseAbs().colwise().sum().maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:133:14: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, -1, 2, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix >, -1, 2, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix >, -1, 2, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::Matrix >, -1, 2, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::Matrix >, -1, 2, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::Matrix >, -1, 2, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:203:15: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::Matrix >, -1, 2, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Matrix >, -1, 2, true> >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:217:20: required from 'PacketType Eigen::internal::evaluator >::packet(Eigen::Index) const [with int LoadMode = 0; PacketType = __vector(2) double; ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 0; Eigen::Index = long long int]' 217 | PanelEvaluator panel_eval(panel); | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:251:78: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 0>; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix >, Eigen::internal::member_sum, 0> >; Scalar = double]' 251 | PacketScalar packet_res0 = eval.template packet(alignedStart); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 0>; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::PartialReduxExpr, const Eigen::Matrix >, Eigen::internal::member_sum, 0>; typename Eigen::internal::traits::Scalar = double]' 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: [ skipping 4 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::Matrix >, -1, 1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::Matrix >, -1, 1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::Matrix >, -1, 1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:72: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, Eigen::Matrix, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix, 0>, Eigen::Matrix, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix, 0>, Eigen::Matrix, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::Matrix, 0>, Eigen::Matrix, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::Matrix, 0>, Eigen::Matrix, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, true>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Matrix, 0>, Eigen::Transpose >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Matrix, 0>, Eigen::Transpose >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Matrix, 0>, Eigen::Transpose >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]' 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from 'Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]' 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::Matrix; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::Matrix; Func = Eigen::internal::scalar_max_op; Evaluator = Eigen::internal::redux_evaluator >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_max_op; Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:448:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with int NaNPropagation = 0; Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]' 448 | return derived().redux(Eigen::internal::scalar_max_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:466:37: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::maxCoeff() const [with Derived = Eigen::Matrix; typename Eigen::internal::traits::Scalar = double]' 466 | return maxCoeff(); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:511:85: required from 'void Eigen::ColPivHouseholderQR::computeInPlace() [with _MatrixType = Eigen::Matrix]' 511 | RealScalar threshold_helper = numext::abs2(m_colNormsUpdated.maxCoeff() * NumTraits::epsilon()) / RealScalar(rows); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:477:3: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>' 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Block, -1, -1, false>, 1, -1, false> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, -1, false>, 1, -1, false> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gemm_pack_lhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long long int; DataMapper = Eigen::internal::blas_data_mapper; int Pack1 = 4; int Pack2 = 2; Packet = __vector(2) double; bool Conjugate = false; bool PanelMode = true]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularSolverMatrix.h:319:27: required from 'static void Eigen::internal::triangular_solve_matrix::run(Index, Index, const Scalar*, Index, Scalar*, Index, Index, Eigen::internal::level3_blocking&) [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/4.5/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:102:12: required from 'static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; int Side = 2; int Mode = 2]' 100 | triangular_solve_matrix | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 102 | ::run(size, othersize, &actualLhs.coeffRef(0,0), actualLhs.outerStride(), &rhs.coeffRef(0,0), rhs.innerStride(), rhs.outerStride(), blocking); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: required from 'void Eigen::TriangularViewImpl<_MatrixType, _Mode, Eigen::Dense>::solveInPlace(const Eigen::MatrixBase&) const [with int Side = 2; OtherDerived = Eigen::Block, -1, -1, false>; _MatrixType = const Eigen::Transpose, -1, -1, false> >; unsigned int _Mode = 2]' 181 | internal::triangular_solver_selector::type, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 182 | Side, Mode>::run(derived().nestedExpression(), otherCopy); | ~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:364:96: required from 'static Eigen::Index Eigen::internal::llt_inplace::blocked(MatrixType&) [with MatrixType = Eigen::Matrix; Scalar = double; Eigen::Index = long long int]' 364 | if(rs>0) A11.adjoint().template triangularView().template solveInPlace(A21); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:408:68: required from 'static bool Eigen::internal::LLT_Traits::inplace_decomposition(MatrixType&) [with MatrixType = Eigen::Matrix]' 408 | { return llt_inplace::blocked(m)==-1; } | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:456:42: [ skipping 2 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/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::half>::half QuarterPacket; | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::size, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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::size, | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> >, Eigen::Transpose, -1, -1, false> > >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >, Eigen::Transpose, -1, -1, false> > >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >, Eigen::Transpose, -1, -1, false> > >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1, false> >, Eigen::Transpose, -1, -1, false> > >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1, false> >, Eigen::Transpose, -1, -1, false> > >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1, false> >, Eigen::Transpose, -1, -1, false> > >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> > >, -1, 1, true>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false> > >, -1, 1, true>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false> > >, -1, 1, true>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false> > >, -1, 1, true>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 1, -1, true>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 1, -1, true>, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >, 1, -1, true>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >, 1, -1, true>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false> >, 1, -1, true>, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false> >, 1, -1, true>, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Transpose > > >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Transpose > > >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Transpose > > >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Transpose > > >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Transpose > > >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Transpose > > >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > > >, -1, 1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > > >, -1, 1, false>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > > >, -1, 1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > > >, -1, 1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase > > >, -1, 1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense > > >, -1, 1, false>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, 1, -1, false>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > >, 1, -1, false>, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, 1, -1, false>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, 1, -1, false>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase > >, 1, -1, false>, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense > >, 1, -1, false>, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:29:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:113:15: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>' 113 | LhsNested m_lhs; | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:29:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 2, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Matrix, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Matrix, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Matrix, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Matrix, 2, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Matrix, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Matrix, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:610:38: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long long int]' 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::CopyConstructible<__gnu_cxx::__normal_iterator > >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]' 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept_check.hpp:167:5: required from 'struct boost::CopyConstructible<__gnu_cxx::__normal_iterator > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:125:16: required from 'struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >' 125 | struct IncrementableIteratorConcept : CopyConstructible | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >' 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::CopyConstructible::~CopyConstructible() [with TT = __gnu_cxx::__normal_iterator >]' 37 | ~model() | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]' 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept_check.hpp:208:5: required from 'struct boost::Convertible' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::incrementable_traversal_tag]' 37 | ~model() | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]' 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:136:13: required from 'struct boost::range_detail::IncrementableIteratorConcept<__gnu_cxx::__normal_iterator > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >' 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied > > >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::range_detail::IncrementableIteratorConcept::~IncrementableIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]' 37 | ~model() | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::EqualityComparable<__gnu_cxx::__normal_iterator > >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]' 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept_check.hpp:233:5: required from 'struct boost::EqualityComparable<__gnu_cxx::__normal_iterator > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:147:16: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >' 147 | struct SinglePassIteratorConcept | ^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied > > >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::EqualityComparable::~EqualityComparable() [with TT = __gnu_cxx::__normal_iterator >]' 37 | ~model() | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::Convertible]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements >]' 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept_check.hpp:208:5: required from 'struct boost::Convertible' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::Convertible]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::Convertible::~Convertible() [with X = boost::iterators::random_access_traversal_tag; Y = boost::iterators::single_pass_traversal_tag]' 37 | ~model() | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > >]' 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:158:13: required from 'struct boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::range_detail::SinglePassIteratorConcept<__gnu_cxx::__normal_iterator > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied > > >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied > > >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::range_detail::SinglePassIteratorConcept::~SinglePassIteratorConcept() [with Iterator = __gnu_cxx::__normal_iterator >]' 37 | ~model() | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp: In instantiation of 'boost::concepts::usage_requirements::~usage_requirements() [with Model = boost::SinglePassRangeConcept > > >]': D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:50:47: required from 'static void boost::concepts::requirement::failed() [with Model = boost::concepts::usage_requirements > > > >]' 50 | static void failed() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/range/concepts.hpp:284:9: required from 'struct boost::SinglePassRangeConcept > > >' 92 | &::boost::concepts::requirement_::failed> \ | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:32:62: required by substitution of 'template boost::concepts::detail::yes boost::concepts::detail::has_constraints_(Model*, wrap_constraints*) [with Model = boost::SinglePassRangeConcept > > >]' 32 | inline yes has_constraints_(Model*, wrap_constraints* = 0); | ^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:42:5: required from 'const bool boost::concepts::not_satisfied > > > >::value' 44 | , value = sizeof( detail::has_constraints_((Model*)0) ) == sizeof(detail::yes) ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/has_constraints.hpp:45:51: required from 'struct boost::concepts::not_satisfied > > > >' 45 | typedef boost::integral_constant type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/detail/general.hpp:72:8: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/iterator/iterator_facade.hpp:982:3: required from 'typename boost::iterators::detail::enable_if_interoperable::type>::type boost::iterators::operator!=(const iterator_facade&, const iterator_facade&) [with Derived1 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V1 = std::__cxx11::basic_string; TC1 = forward_traversal_tag; Reference1 = std::__cxx11::basic_string; Difference1 = long long int; Derived2 = transform_iterator, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; V2 = std::__cxx11::basic_string; TC2 = forward_traversal_tag; Reference2 = std::__cxx11::basic_string; Difference2 = long long int; typename detail::enable_if_interoperable::type>::type = bool; typename boost::mpl::apply2::type = bool]' 966 | return_prefix iterator_core_access::base_op( \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 967 | *static_cast(&lhs) \ | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 968 | , *static_cast(&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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >]' 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, __gnu_cxx::__normal_iterator > >, boost::algorithm::split_iterator<__gnu_cxx::__normal_iterator > >, boost::use_default, boost::use_default>; = void; _Tp = std::__cxx11::basic_string; _Alloc = std::allocator >; allocator_type = std::allocator >]' 711 | _M_range_initialize(__first, __last, | ~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~ 712 | std::__iterator_category(__first)); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/algorithm/string/iter_find.hpp:186:0: required from 'SequenceSequenceT& boost::algorithm::iter_split(SequenceSequenceT&, RangeT&&, FinderT) [with SequenceSequenceT = std::vector >; RangeT = std::__cxx11::basic_string&; FinderT = detail::token_finderF >]' 186 | SequenceSequenceT Tmp(itBegin, itEnd); D:/RCompile/CRANpkg/lib/4.5/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 >; RangeT = std::__cxx11::basic_string&; PredicateT = detail::is_any_ofF]' 158 | return ::boost::algorithm::iter_split( 159 | Result, 160 | Input, 161 | ::boost::algorithm::token_finder( Pred, eCompress ) ); D:/RCompile/CRANpkg/lib/4.5/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/4.5/BH/include/boost/concept/usage.hpp:20:48: warning: 'this' pointer is null [-Wnonnull] 20 | ~usage_requirements() { ((Model*)0)->~Model(); } | ~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/BH/include/boost/concept/usage.hpp:37:7: note: in a call to non-static member function 'boost::SinglePassRangeConcept::~SinglePassRangeConcept() [with T = const boost::iterator_range<__gnu_cxx::__normal_iterator > >]' 37 | ~model() | ^ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]' 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Core:166: D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:89:68: required from 'static void Eigen::internal::selfadjoint_matrix_vector_product::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/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: required from 'static void Eigen::internal::selfadjoint_product_impl::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Scalar = double]' 227 | internal::selfadjoint_matrix_vector_product::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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:805:109: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; int ProductTag = 7; Scalar = double]' 805 | selfadjoint_product_impl::run(dst, lhs.nestedExpression(), rhs, alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from 'static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>; Scalar = double]' 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from 'static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block, -1, 1, false>; Lhs = Eigen::SelfAdjointView, -1, -1, false>, 1>; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >; Derived = Eigen::internal::generic_product_impl, -1, -1, false>, 1>, Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >, Eigen::SelfAdjointShape, Eigen::DenseShape, 7>]' 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:369:35: required from 'void Eigen::internal::tridiagonalization_inplace(MatrixType&, CoeffVectorType&) [with MatrixType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 369 | hCoeffs.tail(n-i-1).noalias() = (matA.bottomRightCorner(remainingSize,remainingSize).template selfadjointView() | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 370 | * (conj(h) * matA.col(i).tail(remainingSize))); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:449:31: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 449 | tridiagonalization_inplace(mat, hCoeffs); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/Memory.h:500:60: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 500 | return first_aligned::alignment>(array, size); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:167:27: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, 1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, 1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:170:53: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, 1, false> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:170:34: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, 1, false> >, Eigen::Block, -1, -1, false>, -1, -1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:129:41: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:132:29: required from 'void Eigen::MatrixBase::applyHouseholderOnTheLeft(const EssentialPart&, const Scalar&, Scalar*) [with EssentialPart = Eigen::Block, -1, 1, false>; Derived = Eigen::Block, -1, -1, false>; Scalar = double]' 132 | bottom.noalias() -= tau * essential * tmp; | ~~~~^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/HouseholderSequence.h:307:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 5>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, false> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:132:41: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Matrix; Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int Options = 0; Scalar = double; SrcXprType = Eigen::Product >, Eigen::Matrix, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; Src = Eigen::Product >, Eigen::Matrix, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Matrix, 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/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:22:0: required from here 22 | vector_d eigenprojections = eigenvectors.transpose() * g; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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, 0>; _Scalar = double; int _Rows = -1; int _Cols = 1; int _Options = 0; int _MaxRows = -1; int _MaxCols = 1]' 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>; Func = assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 850 | typename plain_matrix_type::type tmp(src); | ^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from 'void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Matrix; Src = Eigen::Product, Eigen::Matrix, 0>]' 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:779:32: required from 'Derived& Eigen::PlainObjectBase::_set(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 0>; Derived = Eigen::Matrix]' 779 | internal::call_assignment(this->derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::Product, Eigen::Matrix, 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/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:26:0: required from here 26 | g = eigenvectors * eigenprojections; D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose >; Rhs = Eigen::Transpose > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose > >; CoeffReturnType = double; Eigen::Index = long long int]' 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 1, -1, false>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:88:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 88 | lp -= 0.5 * nu_ref * log_determinant_ldlt(ldlt_S); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:610:38: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:88:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 88 | lp -= 0.5 * nu_ref * log_determinant_ldlt(ldlt_S); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:114:15: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Matrix; Rhs = Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Solve >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Solve >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >' 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, double>' 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from 'class Eigen::internal::visitor_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> > >' 79 | CoeffReadCost = internal::evaluator::CoeffReadCost | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:564:45: required from 'struct Eigen::internal::unary_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >, Eigen::internal::IndexBased, double>' 564 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Visitor.h:79:51: required from 'class Eigen::internal::visitor_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> > >' 79 | CoeffReadCost = internal::evaluator::CoeffReadCost | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Visitor.h:123:17: required from 'void Eigen::DenseBase::visit(Visitor&) const [with Visitor = Eigen::internal::max_coeff_visitor, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >, 0>; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false> >]' 123 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Visitor.h:374:14: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseUnaryOp, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:98:46: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::squaredNorm() const [with Derived = Eigen::Block, -1, 1, true>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 98 | return numext::real((*this).cwiseAbs2().sum()); | ~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:110:23: required from 'typename Eigen::NumTraits::Scalar>::Real Eigen::MatrixBase::norm() const [with Derived = Eigen::Block, -1, 1, true>; typename Eigen::NumTraits::Scalar>::Real = double; typename Eigen::internal::traits::Scalar = double]' 110 | return numext::sqrt(squaredNorm()); | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:507:52: [ skipping 3 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false>, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 1, -1, false>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 1, -1, false>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false> > > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1, false> > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1, false> > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1, false> >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1, false> >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > > > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl > > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose > > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > >, 1, -1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl > >, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose > >, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:67: required from 'Derived& Eigen::DenseBase::operator/=(const Scalar&) [with Derived = Eigen::Block, 1, 1, false>; Scalar = double]' 41 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:599:18: required from 'void Eigen::LDLT::_solve_impl_transposed(const RhsType&, DstType&) const [with bool Conjugate = true; RhsType = Eigen::Matrix; DstType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 599 | dst.row(i) /= vecD(i); | ~~~~~~~~~~~^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:569:31: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>; U = Eigen::Block >, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block >, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true>, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, true>, 1, -1, true>; U = Eigen::Block >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block >, -1, 1, true>; Derived = Eigen::Block, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h: In instantiation of 'void Eigen::internal::gemm_pack_rhs::operator()(Scalar*, const DataMapper&, Index, Index, Index, Index) [with Scalar = double; Index = long long int; DataMapper = Eigen::internal::const_blas_data_mapper; int nr = 4; bool Conjugate = false; bool PanelMode = true]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:346:25: required from 'static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [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/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Dest::Scalar = double]' 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; int ProductTag = 8; Scalar = double]' 783 | triangular_product_impl::run(dst, lhs, rhs.nestedExpression(), alpha); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:361:27: required from 'static void Eigen::internal::generic_product_impl_base::scaleAndAddTo(Dst&, const Lhs&, const Rhs&, const Scalar&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, Eigen::DenseShape, Eigen::TriangularShape, 8>; Scalar = double]' 361 | { Derived::scaleAndAddTo(dst,lhs,rhs,alpha); } | ~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:349:33: required from 'static void Eigen::internal::generic_product_impl_base::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>; Derived = Eigen::internal::generic_product_impl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, Eigen::DenseShape, Eigen::TriangularShape, 8>]' 349 | { dst.setZero(); scaleAndAddTo(dst, lhs, rhs, Scalar(1)); } | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]' 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralBlockPanelKernel.h:2459:62: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 2459 | PacketBlock kernel; | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1, false> >, 6>, Eigen::Block, -1, -1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:99:96: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 2>, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 2>, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 2>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 2>, Eigen::Matrix, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 2>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 2>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:101:66: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 1>, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 1>, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 1>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, 1>, Eigen::Matrix, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, 1>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, 1>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:102:66: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, 5>, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, 5>, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, 5>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1, false>, 5>, Eigen::Matrix, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1, false>, 5>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1, false>, 5>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:103:22: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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; TranspositionType = Eigen::Transpositions<-1, -1, int>; Workspace = Eigen::Matrix]' 361 | A21.noalias() -= A20 * temp.head(k); | ~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:526:51: required from 'Eigen::LDLT<_MatrixType, _UpLo>& Eigen::LDLT::compute(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 526 | m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success : NumericalIssue; | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:120:14: required from 'Eigen::LDLT::LDLT(const Eigen::EigenBase&) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix; int _UpLo = 1]' 120 | compute(matrix.derived()); | ~~~~~~~^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:683:10: required from 'const Eigen::LDLT::PlainObject> Eigen::MatrixBase::ldlt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 683 | return LDLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; stan::require_matrix_t* = 0]' 45 | Eigen::LDLT cholesky = value_of_rec(y_ref).ldlt(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block > >, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block > >, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>, 1, -1, true>; U = Eigen::Block > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block > >, -1, 1, true>; Derived = Eigen::Block >, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, -1, 1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, -1, 1, false>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> > >, Eigen::Matrix, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> > >, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::OuterStride<> >, 1, -1, true>; SrcXprType = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>; Functor = swap_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>; SrcXprType = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>; Functor = Eigen::internal::swap_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::OuterStride<> >, 1, -1, true>; Src = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>; Func = swap_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>; Src = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>; Func = swap_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:424:22: required from 'void Eigen::DenseBase::swap(const Eigen::DenseBase&) [with OtherDerived = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>; Derived = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>]' 424 | call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:483:24: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::OuterStride<> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::OuterStride<> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::OuterStride<> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, 0, Eigen::OuterStride<> >, -1, 1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl, 0, Eigen::OuterStride<> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Ref, 0, Eigen::OuterStride<> >; Lhs = Eigen::Ref, 0, Eigen::OuterStride<> >; Rhs = Eigen::Ref, 0, Eigen::OuterStride<> >; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:464:20: required from 'static void Eigen::internal::generic_product_impl::subTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Ref, 0, Eigen::OuterStride<> >; Lhs = Eigen::Ref, 0, Eigen::OuterStride<> >; Rhs = Eigen::Ref, 0, Eigen::OuterStride<> >]' 464 | scaleAndAddTo(dst, lhs, rhs, Scalar(-1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref, 0, Eigen::OuterStride<> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref, 0, Eigen::OuterStride<> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref, 0, Eigen::OuterStride<> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref, 0, Eigen::OuterStride<> >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref, 0, Eigen::OuterStride<> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref, 0, Eigen::OuterStride<> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Ref, 0, Eigen::OuterStride<> >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Ref, 0, Eigen::OuterStride<> >; Lhs = Eigen::Ref, 0, Eigen::OuterStride<> >; Rhs = Eigen::Ref, 0, Eigen::OuterStride<> >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:464:20: required from 'static void Eigen::internal::generic_product_impl::subTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Ref, 0, Eigen::OuterStride<> >; Lhs = Eigen::Ref, 0, Eigen::OuterStride<> >; Rhs = Eigen::Ref, 0, Eigen::OuterStride<> >]' 464 | scaleAndAddTo(dst, lhs, rhs, Scalar(-1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose >, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose >, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose >, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose >, 2, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose >, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Transpose >, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:234:28: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose >, Eigen::Transpose > > >; _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/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:42:17: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(A) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | .transpose() | ~~~~~~~~~~~~ 39 | .lu() | ~~~~~ 40 | .solve(Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix, 0>, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix, 0>, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Matrix, 0>, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Matrix, 0>, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Matrix, 0>, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl > >, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block > >, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block > >, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true>, -1, 1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true>, -1, 1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, true>, -1, 1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, false>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: required from 'Derived& Eigen::MatrixBase::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Block, -1, 1, true>, -1, 1, false>, 0>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 66 | internal::call_assignment(derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/to_vector.hpp:22:11: required from 'Eigen::Matrix::type, -1, 1> stan::math::to_vector(const EigMat&) [with EigMat = Eigen::Product, Eigen::Block, -1, 1, true>, -1, 1, false>, 0>; stan::require_eigen_t* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true>, -1, 1, false> >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true>, -1, 1, false> >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, true>, -1, 1, false> >, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, true>, -1, 1, false> >, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, -1, -1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = div_assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = Eigen::internal::div_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:28: required from 'Derived& Eigen::DenseBase::operator/=(const Scalar&) [with Derived = Eigen::Block, -1, -1, false>, -1, 1, false>; Scalar = double]' 41 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:333:21: [ skipping 5 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >, 1, -1, true>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >, 1, -1, true>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1, false> >, 1, -1, true>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1, false> >, 1, -1, true>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false> >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, -1, -1, false> > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block > >, 1, -1, false>; U = Eigen::Block > > >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, 1, -1, false>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > >, 1, -1, false>, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, 1, -1, false>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, 1, -1, false>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl > >, 1, -1, false>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose > >, 1, -1, false>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block > > >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block > > >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block > > >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block > > >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block > > >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block > > >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Diagonal, 0>; Scalar = double]' 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from 'Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Diagonal, 0>]' 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]' 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, true>, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, true>, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, -1, 1, true>, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, 1, true>, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1, false>, -1, 1, true>, -1, 1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:63:90: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; VectorsType = Eigen::Block, -1, -1, false>; CoeffsType = Eigen::VectorBlock, -1>]' 63 | triFactor.row(i).tail(rt).noalias() = -hCoeffs(i) * vectors.col(i).tail(rs).adjoint() | ~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::TriangularView, -1, -1, false>, -1, -1, false>, 5>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:64:57: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; VectorsType = Eigen::Block, -1, -1, false>; CoeffsType = Eigen::VectorBlock, -1>]' 73 | triFactor.row(i).tail(nbVecs-j-1) += z * triFactor.row(j).tail(nbVecs-j-1); | ~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/BlockHouseholder.h:92:55: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 40 | _Hk = Hupd * _Hk * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 40 | _Hk = Hupd * _Hk * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, Eigen::Matrix, 0>, 1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, Eigen::Matrix, 0>, 1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 40 | _Hk = Hupd * _Hk * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Product, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, Eigen::Matrix, 0>; Rhs = Eigen::Transpose >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 40 | _Hk = Hupd * _Hk * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; Dest = Eigen::Block, -1, 1, true>; typename Dest::Scalar = double]' 366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Dest = Eigen::Block, 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/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Dest = Eigen::Block, 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/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >; Rhs = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; Dest = Eigen::Block, -1, 1, true>; typename Dest::Scalar = double]' 366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Dest = Eigen::Block, 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/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 1, -1, false>; Rhs = Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Dest = Eigen::Block, 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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::CwiseUnaryView, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:610:38: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 2>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 2> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 2> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 2, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 2, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::CwiseUnaryOp, -1, 1>&>(const Eigen::Matrix, -1, 1>&)::::, const Eigen::Matrix, -1, 1> >, 2>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:577:26: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::Matrix >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Matrix >, -1, 1, false> >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::Block, const Eigen::Matrix >, -1, 1, false>; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::Block, const Eigen::Matrix >, -1, 1, false>; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorwiseOp.h:114:1: required from 'ResultType Eigen::internal::member_sum::operator()(const XprType&) const [with XprType = Eigen::Block, const Eigen::Matrix >, -1, 1, false>; ResultType = double; Scalar = double]' 97 | { return mat.MEMBER(); } \ | ~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PartialReduxEvaluator.h:183:21: required from 'const Eigen::internal::evaluator >::Scalar Eigen::internal::evaluator >::coeff(Eigen::Index) const [with ArgType = const Eigen::CwiseUnaryOp, const Eigen::Matrix >; MemberOp = Eigen::internal::member_sum; int Direction = 0; Scalar = double; Eigen::Index = long long int]' 183 | return m_functor(m_arg.template subVector(index)); | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:268:34: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::OuterStride<> >, -1, -1, false>; Lhs = Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>; Rhs = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>; Func = generic_product_impl, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::DenseShape, Eigen::DenseShape, 5>::sub]' 639 | bool MapExternalBuffer = nested_eval::Evaluate && Xpr::MaxSizeAtCompileTime==Dynamic | ~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:329:41: required from 'static void Eigen::internal::generic_product_impl::subTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Block, 0, Eigen::OuterStride<> >, -1, -1, false>; Lhs = Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>; Rhs = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>]' 329 | internal::outer_product_selector_run(dst, lhs, rhs, sub(), is_row_major()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:178:42: required from 'static void Eigen::internal::Assignment, Eigen::internal::sub_assign_op, 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&) [with DstXprType = Eigen::Block, 0, Eigen::OuterStride<> >, -1, -1, false>; Lhs = Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>; Rhs = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>]' 178 | generic_product_impl::subTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::OuterStride<> >, -1, -1, false>; Src = Eigen::Product, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>; Func = sub_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/NoAlias.h:59:31: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::OuterStride<> >, -1, -1, false>; Lhs = Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>; Rhs = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>; Func = generic_product_impl, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, false>, Eigen::Block, 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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:329:41: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, Eigen::Ref, 0, Eigen::OuterStride<> >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, Eigen::Ref, 0, Eigen::OuterStride<> >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, Eigen::Ref, 0, Eigen::OuterStride<> >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::OuterStride<> >, Eigen::Ref, 0, Eigen::OuterStride<> >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::OuterStride<> >, Eigen::Ref, 0, Eigen::OuterStride<> >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::OuterStride<> >, Eigen::Ref, 0, Eigen::OuterStride<> >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1, false>, -1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true>, -1, 1, false> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true>, -1, 1, false> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, 1, true>, -1, 1, false> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, 1, true>, -1, 1, false> > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false> >, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false> >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false> >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, false> >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 1, -1, false> >, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, -1, -1, false>, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, false>, 1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, 1, -1, false> >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, 1, -1, false> >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, 1, -1, false> >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false>, 1, -1, false> >, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, -1, 1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, -1, 1, false>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 1, -1, false>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Matrix; stan::require_eigen_vt* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix; Rhs = const Eigen::Transpose >; typename Dest::Scalar = double]' 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 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/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]' 18 | return std::forward(a); | ^ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 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/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]' 18 | return std::forward(a); | ^ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 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/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]' 18 | return std::forward(a); | ^ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = false; Lhs = Eigen::Matrix; Rhs = const Eigen::Transpose >; typename Dest::Scalar = double]' 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 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/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]' 18 | return std::forward(a); | ^ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:22:57: required from 'struct Eigen::internal::traits >' 22 | typedef typename find_best_packet<_Scalar,size>::type PacketScalar; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: required from 'class Eigen::Matrix' 178 | class Matrix | ^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:150:68: required from 'static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [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 triangularBuffer(a); | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]' 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h: In instantiation of 'struct Eigen::internal::find_best_packet': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:179:81: required from 'class Eigen::DenseBase, 0> >' 179 | typedef typename internal::find_best_packet::type PacketScalar; | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:153:32: required from 'static void Eigen::internal::product_triangular_matrix_matrix::run(Index, Index, Index, const Scalar*, Index, const Scalar*, Index, Scalar*, Index, Index, const Scalar&, Eigen::internal::level3_blocking&) [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/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:443:12: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Dest::Scalar = double]' 438 | internal::product_triangular_matrix_matrix::Flags&RowMajorBit) ? RowMajor : ColMajor, LhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 441 | (internal::traits::Flags&RowMajorBit) ? RowMajor : ColMajor, RhsBlasTraits::NeedToConjugate, | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 442 | (internal::traits::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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:44: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 190 | bool Stop = Size==Dynamic || (Size%unpacket_traits::size)==0 || is_same::half>::value> | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:190:83: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:208:88: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 208 | typedef typename find_best_packet_helper::type>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, -1, 1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:148:43: required from 'static void Eigen::internal::Assignment, Eigen::internal::assign_op, Eigen::internal::Dense2Dense, typename Eigen::internal::enable_if<((Options == Eigen::DefaultProduct) || (Options == Eigen::AliasFreeProduct))>::type>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; Lhs = Eigen::Block, -1, -1, false>, -1, -1, false>; Rhs = Eigen::Block, -1, 1, false>; int Options = 0; Scalar = double; SrcXprType = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>]' 148 | generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; Src = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/NoAlias.h:43:31: required from 'ExpressionType& Eigen::NoAlias::operator=(const StorageBase&) [with OtherDerived = Eigen::Product, -1, -1, false>, -1, -1, false>, Eigen::Block, -1, 1, false>, 0>; ExpressionType = Eigen::Map, 0, Eigen::Stride<0, 0> >; StorageBase = Eigen::MatrixBase]' 43 | call_assignment_no_alias(m_expression, other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:167:19: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long long int]' 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:769:69: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:37:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 37 | _Hk.noalias() = ((1.0 / B0fact) * Hupd) * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0>, Eigen::Transpose >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, Eigen::Transpose >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 0>, Eigen::Transpose >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 40 | _Hk = Hupd * _Hk * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 40 | _Hk = Hupd * _Hk * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 38 | arena_t res = arena_A_val * arena_B_val; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:370:45: required from 'struct Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::DenseShape, Eigen::DenseShape, 7>' 370 | typedef typename nested_eval::type RhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:479:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scalar = double]' 478 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 479 | ::scaleAndAddTo(dst_vec, a_lhs, a_rhs.col(0), alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >; Dest = Eigen::Transpose, 1, -1, false> >; typename Dest::Scalar = double]' 379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >; Dest = Eigen::Transpose, 1, -1, false> >; typename Dest::Scalar = double]' 379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:366:52: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >; Rhs = Eigen::Transpose, 1, -1, false> >; Dest = Eigen::Transpose, 1, -1, false> >; typename Dest::Scalar = double]' 366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:12: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >; Dest = Eigen::Transpose >; typename Dest::Scalar = double]' 379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase >, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase >, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::OuterStride<> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::OuterStride<> > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:26: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::OuterStride<> >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose > >, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: required from 'Derived& Eigen::MatrixBase::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Block, -1, 1, true>, -1, 1, false>, 0>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 66 | internal::call_assignment(derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/to_vector.hpp:22:11: required from 'Eigen::Matrix::type, -1, 1> stan::math::to_vector(const EigMat&) [with EigMat = Eigen::Product, Eigen::Block, -1, 1, true>, -1, 1, false>, 0>; stan::require_eigen_t* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true>, -1, 1, false> >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true>, -1, 1, false> >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, 1, true>, -1, 1, false> >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, true>, -1, 1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false> >, 1, -1, true>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false> >, 1, -1, true>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, -1, false> >, 1, -1, true>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false> >, 1, -1, true>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Block, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Block, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Block, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::Product, Eigen::Matrix, 0>; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3272:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false>, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 1, -1, false>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 1, -1, false>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::Product, Eigen::Matrix, 0>; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3272:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator > > >, -1, 1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator > > >, -1, 1, false>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator > >, 1, -1, false>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator > >, 1, -1, false>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator > >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator > >, 1, -1, false>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator > >, 1, -1, false>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block > > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:125:66: required from 'static void Eigen::internal::triangular_solve_vector::run(Index, const LhsScalar*, Index, RhsScalar*) [with LhsScalar = double; RhsScalar = double; Index = long long int; int Mode = 5; bool Conjugate = false]' 125 | Map >(rhs+s,r) -= rhs[i] * cjLhs.col(i).segment(s,r); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Map.h:94:79: required from 'class Eigen::Map, 0, Eigen::OuterStride<> >' 94 | template class Map | ^~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:72: required from 'static void Eigen::internal::triangular_solve_vector::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 >(rhs+s,k))).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 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/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]' 18 | return std::forward(a); | ^ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 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/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]' 18 | return std::forward(a); | ^ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose >; CoeffReturnType = double; Eigen::Index = long long int]' 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from 'void Eigen::internal::generic_dense_assignment_kernel::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator >; SrcEvaluatorTypeT = Eigen::internal::evaluator, Eigen::Transpose >, 1> >; Functor = Eigen::internal::assign_op; 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/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]' 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/TriangularMatrix.h:856:103: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Functor = Eigen::internal::add_assign_op]' 856 | call_triangular_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::TriangularShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/EigenBase.h:145:18: required from 'Derived& Eigen::DenseBase::operator+=(const Eigen::EigenBase&) [with OtherDerived = Eigen::TriangularView, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::TriangularView, 0, Eigen::Stride<0, 0> >, 1>, 0>, 1>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 145 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 31 | arena_L.adj() += ((res.adj().transpose() + res.adj()) 32 | * arena_L_val.template triangularView()) 33 | .template triangularView(); D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose >; Rhs = Eigen::Transpose > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose > >; CoeffReturnType = double; Eigen::Index = long long int]' 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from 'void Eigen::internal::generic_dense_assignment_kernel::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator >; SrcEvaluatorTypeT = Eigen::internal::evaluator >, Eigen::Transpose > >, 1> >; Functor = Eigen::internal::assign_op; 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/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:797:41: required from 'Derived& Eigen::PlainObjectBase::_set_noalias(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 797 | internal::call_assignment_no_alias(this->derived(), other.derived(), internal::assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 0>; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Product >, Eigen::Transpose > >, 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/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:29:18: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 29 | return M_ref * M_ref.transpose(); | ~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_t* = 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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:44:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 44 | arena_B.adj() += arena_A_val.transpose() * res.adj_op(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Dest = Eigen::Matrix; typename Dest::Scalar = double]' 366 | dest += (alpha*actual_rhs.coeff(k)) * lhs.col(k); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 0, Eigen::Stride<0, 0> >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Map, 0, Eigen::Stride<0, 0> >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>; U = Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Product >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; CoeffReturnType = double; Eigen::Index = long long int]' 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Matrix; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, const Eigen::Block, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, const Eigen::Block, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, const Eigen::Block, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, const Eigen::Block, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, const Eigen::Block, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, const Eigen::Block, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> >; stan::require_dense_dynamic_t* = 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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T4__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 1, -1, true>, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 1, -1, true>, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 1, -1, true>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, 1, -1, true>, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, 1, -1, true>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, 1, -1, true>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> >; stan::require_dense_dynamic_t* = 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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T4__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, 1, -1, false>; U = Eigen::Block, 1, -1, false> >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false>, 1, -1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, false>, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, false>, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Transpose, -1, -1, false> > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose, -1, -1, false> >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose, -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/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::Product, Eigen::Matrix, 0>; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3272:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block > > >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose > >; Rhs = Eigen::Transpose > > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose > > >; CoeffReturnType = double; Eigen::Index = long long int]' 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Transpose >; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:3306:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, 1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = div_assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = Eigen::internal::div_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, 1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:28: required from 'Derived& Eigen::DenseBase::operator/=(const Scalar&) [with Derived = Eigen::Block, 1, 1, false>; Scalar = double]' 41 | internal::call_assignment(this->derived(), PlainObject::Constant(rows(),cols(),other), internal::div_assign_op()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:599:18: [ skipping 8 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]' 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from 'Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]' 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Diagonal, 0>; Scalar = double]' 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from 'Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Diagonal, 0>]' 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block, -1, -1, false>, -1, 1, true>; Functor = add_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::Block, -1, -1, false>, -1, 1, true>; Functor = Eigen::internal::add_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, -1, -1, false>, -1, 1, true>; Func = add_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Map, 0, Eigen::Stride<0, 0> >; Src = Eigen::Block, -1, -1, false>, -1, 1, true>; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from 'Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, -1, -1, false>, -1, 1, true>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Householder/Householder.h:168:9: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 40 | _Hk = Hupd * _Hk * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 40 | _Hk = Hupd * _Hk * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 40 | _Hk = Hupd * _Hk * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 40 | _Hk = Hupd * _Hk * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector, -1, -1>, std::allocator, -1, -1> > >; bool Jacobian = true; LP = stan::math::var_value; Sizes = {int}; stan::require_std_vector_t* = 0; T = stan::math::var_value; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, Jacobian>( 980 | lp, sizes...)); stanExports_stanmarg.h:12986:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12984 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix< 12985 | std::vector>, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = false; Lhs = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Map, 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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector, -1, -1>, std::allocator, -1, -1> > >; bool Jacobian = true; LP = stan::math::var_value; Sizes = {int}; stan::require_std_vector_t* = 0; T = stan::math::var_value; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, Jacobian>( 980 | lp, sizes...)); stanExports_stanmarg.h:12986:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12984 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix< 12985 | std::vector>, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 38 | arena_t res = arena_A_val * arena_B_val; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:38:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 38 | arena_t res = arena_A_val * arena_B_val; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:68:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 68 | arena_t res = arena_A.val_op() * arena_B; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -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::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -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/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > > >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -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::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -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/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose > > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose > > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose > >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >, 1, -1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = div_assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = Eigen::internal::div_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >, 1, -1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:28: required from 'Derived& Eigen::DenseBase::operator/=(const Scalar&) [with Derived = Eigen::Block, 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()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:599:18: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:88:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 88 | lp -= 0.5 * nu_ref * log_determinant_ldlt(ldlt_S); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -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::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -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/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose >, Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Functor = add_assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::add_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from 'Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Derived = Eigen::Block, -1, 1, false>]' 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:296:25: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, const Eigen::Block, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, const Eigen::Block, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, const Eigen::Block, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, const Eigen::Block, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, const Eigen::Block, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, const Eigen::Block, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, 1, -1, false>, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, 1, -1, false>, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, 1, -1, false>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, 1, -1, false>, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, 1, -1, false>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, 1, -1, false>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: required from 'Derived& Eigen::MatrixBase::operator=(const Eigen::DenseBase&) [with OtherDerived = Eigen::Product, Eigen::Block, -1, 1, true>, -1, 1, false>, 0>; Derived = Eigen::Map, 0, Eigen::Stride<0, 0> >]' 66 | internal::call_assignment(derived(), other.derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/to_vector.hpp:22:11: required from 'Eigen::Matrix::type, -1, 1> stan::math::to_vector(const EigMat&) [with EigMat = Eigen::Product, Eigen::Block, -1, 1, true>, -1, 1, false>, 0>; stan::require_eigen_t* = 0; typename stan::value_type::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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> >, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, true>, -1, 1, false> >, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 13 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::Matrix, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::Matrix, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::Matrix, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base >, Eigen::Matrix, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl >, Eigen::Matrix, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product >, Eigen::Matrix, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> >; stan::require_dense_dynamic_t* = 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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T4__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 0>, const Eigen::Block >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:4181:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Matrix, 0>, 1, -1, false>, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:4181:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, -1, false> > >, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block, -1, -1, false> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false> >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, -1, -1, false> > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, -1, false> > >, -1, 1, true>; Derived = Eigen::Block, -1, -1, false> >, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 9 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >' 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]' 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from 'Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]' 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 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/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]' 18 | return std::forward(a); | ^ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, -1, 1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false>, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false>, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, false>, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, false>, -1, 1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false> >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, false> >, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, false> >, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:48:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 48 | arena_B.adj() += arena_A_val.transpose() * res_adj; stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose, 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/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> > >, 1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -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/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, 1, -1, true>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> > > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; Rhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >; Dest = Eigen::Transpose, 1, -1, false> >; typename Dest::Scalar = double]' 379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Matrix; Rhs = Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Matrix; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -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/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 1, -1, true> >; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Functor = add_assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose, 1, -1, true> >; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::add_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 1, -1, true> >; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 2, Eigen::Stride<0, 0> > >; Func = add_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:858:27: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, Eigen::Matrix, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > >, Eigen::Matrix, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > >, Eigen::Matrix, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base > >, Eigen::Matrix, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl > >, Eigen::Matrix, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product > >, Eigen::Matrix, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Functor = sub_assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Map, 16, Eigen::Stride<0, 0> > >; Derived = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:305:153: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, -1, false> >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 1, -1, false> >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, 1, -1, false> >, const Eigen::Block, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, false>, 1, -1, false> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, 1, -1, false> >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, -1, false>, 1, -1, false> >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LLT.h:542:10: required from 'const Eigen::LLT::PlainObject> Eigen::MatrixBase::llt() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 542 | return LLT(derived()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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 >; Eigen::MatrixXd = Eigen::Matrix]' 24 | Eigen::LLT 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:70: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0> >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:4192:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::Product, Eigen::Matrix, 0>; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3272:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::Product, Eigen::Matrix, 0>; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3272:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > > >, -1, -1, true>; Derived = Eigen::Block, -1, -1, false>]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:123:0: required from 'stan::math::arena_matrix::type>::value, void>::type>& stan::math::arena_matrix::type>::value, void>::type>::operator=(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 123 | Base::operator=(a); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/arena_matrix.hpp:68:0: required from 'stan::math::arena_matrix::type>::value, void>::type>::arena_matrix(const T&) [with T = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_eigen_t* = 0; MatrixType = Eigen::Matrix; typename std::enable_if::type>::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix]' 68 | *this = other; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/vari.hpp:722:0: required from 'stan::math::vari_value::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type>::vari_value(const S&, bool) [with S = Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::type, typename stan::plain_type::type>, stan::is_eigen_dense_base >::value, void>::type = void; typename std::decay<_Tp>::type = Eigen::Matrix; typename stan::plain_type::type = Eigen::Matrix]' 722 | : val_(x), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/var.hpp:366:0: required from 'stan::math::var_value::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type>::var_value(S&&) [with S = const Eigen::Product, 0, Eigen::Stride<0, 0> >, 1>, Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 0>; stan::require_assignable_t* = 0; T = Eigen::Matrix; typename std::enable_if::value || stan::is_kernel_expression_and_not_scalar::value) && std::is_floating_point::type>::value)>::value, void>::type = void; typename stan::value_type::type = double]' 366 | var_value(S&& x) : vi_(new vari_type(std::forward(x), false)) {} // NOLINT D:/RCompile/CRANpkg/lib/4.5/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 >; stan::require_rev_matrix_t* = 0]' 27 | arena_t res = arena_L_val.template triangularView() D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, 1, false> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, 1, false> > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:207:43: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = add_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 1, -1, true>, 1, -1, false> >; Functor = Eigen::internal::add_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs_update.hpp:40:0: required from 'Scalar stan::optimization::BFGSUpdate_HInv::update(const VectorT&, const VectorT&, bool) [with Scalar = double; int DimAtCompile = -1; VectorT = Eigen::Matrix]' 40 | _Hk = Hupd * _Hk * Hupd.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/bfgs.hpp:246:0: required from 'int stan::optimization::BFGSMinimizer::step() [with FunctorType = stan::optimization::ModelAdaptor; QNUpdateType = stan::optimization::BFGSUpdate_HInv<>; Scalar = double; int DimAtCompile = -1]' 246 | Scalar B0fact = _qn.update(yk, sk, true); D:/RCompile/CRANpkg/lib/4.5/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/4.5/rstan/include/rstan/stan_fit.hpp:517:0: required from 'int rstan::{anonymous}::command(rstan::stan_args&, Model&, Rcpp::List&, const std::vector&, const std::vector >&, RNG_t&) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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/4.5/rstan/include/rstan/stan_fit.hpp:1215:0: required from 'SEXPREC* rstan::stan_fit::call_sampler(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; 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 ::call_sampler) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, 1>, 0, Eigen::Stride<0, 0> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/multiply.hpp:57:0: required from 'auto stan::math::multiply(const T1&, const T2&) [with T1 = Eigen::Matrix, -1, -1>; T2 = Eigen::VectorBlock, -1, -1>, -1, 1, true>, -1>; stan::require_all_matrix_t* = 0; stan::require_return_type_t* = 0; stan::require_not_row_and_col_vector_t* = 0]' 57 | arena_t res = arena_A * arena_B.val_op(); stanExports_stanmarg.h:13638:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >; Functor = add_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >; Functor = Eigen::internal::add_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix, -1, -1>; T3__ = double; T9__ = Eigen::Matrix, -1, 1>; T10__ = Eigen::Matrix, -1, -1>; T11__ = Eigen::Matrix, -1, 1>; T12__ = Eigen::Matrix, -1, -1>; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >, 1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = div_assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, 1, false>; SrcXprType = Eigen::CwiseNullaryOp, Eigen::Matrix >; Functor = Eigen::internal::div_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >, 1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, 0, Eigen::Stride<0, 0> >, 1, 1, false>; Src = Eigen::CwiseNullaryOp, Eigen::Matrix >; Func = div_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SelfCwiseBinaryOp.h:41:28: required from 'Derived& Eigen::DenseBase::operator/=(const Scalar&) [with Derived = Eigen::Block, 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()); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Cholesky/LDLT.h:599:18: [ skipping 11 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, 0, Eigen::Stride<0, 0> > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> model_stanmarg_namespace::multi_normal_suff(const T0__&, const T1__&, const T2__&, const T3__&, const int&, std::ostream*) [with T0__ = Eigen::VectorBlock, -1>; T1__ = Eigen::Block, -1, -1, false>; T2__ = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T3__ = Eigen::Block, -1, -1>, -1, -1, false>; stan::require_all_t, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; stan::promote_args_t::type, typename stan::base_type::type, typename stan::base_type::type, typename stan::base_type::type> = stan::math::var_value; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true> >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Ref, 0, Eigen::OuterStride<> >; Rhs = Eigen::Ref, 0, Eigen::OuterStride<> >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Ref, 0, Eigen::OuterStride<> >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Ref, 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/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, true>, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, true>, -1, 1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Derived = Eigen::Block, -1, 1, true>, -1, 1, false> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:669:10: required from 'const Eigen::ColPivHouseholderQR::PlainObject> Eigen::MatrixBase::colPivHouseholderQr() const [with Derived = Eigen::Matrix; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 669 | return ColPivHouseholderQR(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/log_determinant.hpp:27:31: required from 'stan::value_type_t stan::math::log_determinant(const EigMat&) [with EigMat = Eigen::Matrix; stan::require_eigen_vt* = 0; stan::value_type_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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> >; stan::require_dense_dynamic_t* = 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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T4__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> >; stan::require_dense_dynamic_t* = 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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T4__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >, const Eigen::Map, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularSolverVector.h:78:127: required from 'static void Eigen::internal::triangular_solve_vector::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 >(rhs+s,k))).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:73:12: required from 'static void Eigen::internal::triangular_solver_selector::run(const Lhs&, Rhs&) [with Lhs = const Eigen::Transpose >; Rhs = Eigen::Matrix; int Side = 1; int Mode = 6]' 71 | triangular_solve_vector | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 73 | ::run(actualLhs.cols(), actualLhs.data(), actualLhs.outerStride(), actualRhs); | ~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/SolveTriangular.h:182:21: [ skipping 10 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Func = sub_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, -1, -1, true>; Derived = Eigen::Block, -1, -1, false>]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 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/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]' 18 | return std::forward(a); | ^ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:594:19: required from 'Eigen::PlainObjectBase::PlainObjectBase(const Eigen::DenseBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; Derived = Eigen::Matrix]' 594 | _set_noalias(other); | ~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose, Eigen::TriangularView >, 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/4.5/StanHeaders/include/stan/math/prim/fun/to_ref.hpp:18:27: required from 'stan::ref_type_t stan::math::to_ref(T&&) [with T = const Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >&; stan::ref_type_t = Eigen::Matrix]' 18 | return std::forward(a); | ^ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/tcrossprod.hpp:27:29: required from 'Eigen::Matrix::type, T::RowsAtCompileTime, T::RowsAtCompileTime> stan::math::tcrossprod(const T&) [with T = Eigen::Transpose, Eigen::TriangularView >, 2>, 0> >; stan::require_eigen_vt* = 0; typename stan::value_type::type = double]' 27 | const auto& M_ref = to_ref(M); | ~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Product, Eigen::TriangularView >, 2>, 0>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, -1, false>, -1, -1, false>, 1, -1, false>; U = Eigen::Block, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, false> >, 1, -1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, false> >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, false> >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, 1, false> >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, 1, false> >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, -1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, -1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false>, -1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block, -1, -1, false>; int Mode = 5; bool LhsIsTriangular = true; Lhs = const Eigen::Block, -1, -1, false>; Rhs = Eigen::Matrix; typename Dest::Scalar = double]' 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, Eigen::CwiseNullaryOp, Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, Eigen::CwiseNullaryOp, Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, Eigen::CwiseNullaryOp, Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:86:7: required from 'class Eigen::SolveImpl >, Eigen::CwiseNullaryOp, Eigen::Matrix >, Eigen::Dense>' 86 | class SolveImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Solve.h:62:7: required from 'class Eigen::Solve >, Eigen::CwiseNullaryOp, Eigen::Matrix > >' 62 | class Solve : public SolveImpl::StorageKind> | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/QR/ColPivHouseholderQR.h:644:39: required from 'static void Eigen::internal::Assignment >, Eigen::internal::assign_op::Scalar>, Eigen::internal::Dense2Dense>::run(DstXprType&, const SrcXprType&, const Eigen::internal::assign_op::Scalar>&) [with DstXprType = Eigen::Matrix; MatrixType = Eigen::Matrix; SrcXprType = Eigen::Inverse > >; typename DstXprType::Scalar = double; typename Eigen::ColPivHouseholderQR::Scalar = double]' 644 | dst = src.nestedExpression().solve(MatrixType::Identity(src.rows(), src.cols())); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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, -1, -1>; stan::require_rev_matrix_t* = 0; var = var_value]' 23 | auto arena_m_inv_transpose = to_arena(m_hh.inverse().transpose()); stanExports_stanmarg.h:14144:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> > >, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, -1, 1, false> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 1, -1, false> >; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >; Functor = add_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Transpose, 1, -1, false> >; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > > >, -1, 1, true> >; Functor = Eigen::internal::add_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/wishart_lpdf.hpp:92:0: required from 'stan::return_type_t stan::math::wishart_lpdf(const T_y&, const T_dof&, const T_scale&) [with bool propto = false; T_y = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >; T_dof = int; T_scale = Eigen::Matrix, -1, -1>; stan::require_stan_scalar_t* = 0; stan::require_all_matrix_t* = 0; stan::return_type_t = var_value]' 92 | lp -= 0.5 * trace(mdivide_left_ldlt(ldlt_S, W_ref)); stanExports_stanmarg.h:14327:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14327 | lp_accum__.add(stan::math::wishart_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >; Functor = sub_assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >; Func = sub_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false> >; Derived = Eigen::Block, 0, Eigen::OuterStride<> >, -1, -1, false>, 1, -1, true>]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:305:153: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/LU/PartialPivLU.h:619:10: required from 'const Eigen::PartialPivLU::PlainObject> Eigen::MatrixBase::lu() const [with Derived = Eigen::Transpose >; typename Eigen::DenseBase::PlainObject = Eigen::Matrix]' 619 | return PartialPivLU(eval()); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:39:10: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block > >, 1, -1, false>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose > >, 1, -1, false>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block > >, 1, -1, false>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:4181:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0> >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:4181:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, Eigen::Matrix, 0>, 1, -1, false>; U = Eigen::Block, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0> >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:4192:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false> > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Transpose, -1, -1, false> > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose, -1, -1, false> >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Transpose, -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/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from 'void Eigen::internal::generic_dense_assignment_kernel::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator >; SrcEvaluatorTypeT = Eigen::internal::evaluator, -1, -1, false> >, Eigen::Transpose, -1, -1, false> > >, 1> >; Functor = Eigen::internal::assign_op; 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/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 12 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/crossprod.hpp:21:20: required from 'auto stan::math::crossprod(const EigMat&) [with EigMat = Eigen::Block, -1, -1, false>; stan::require_eigen_t* = 0]' 21 | return tcrossprod(M.transpose()); | ~~~~~~~~~~^~~~~~~~~~~~~~~ stanExports_stanmarg.h:4245:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, const Eigen::Block, -1, 1, true>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, const Eigen::Block, -1, 1, true>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, const Eigen::Block, -1, 1, true>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, const Eigen::Block, -1, 1, true>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, const Eigen::Block, -1, 1, true>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, const Eigen::Block, -1, 1, true>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Matrix, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Matrix, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Matrix, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Matrix, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Matrix, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Matrix, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:113:15: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/util/XprHelper.h:372:102: required from 'struct Eigen::internal::plain_object_eval, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Dense>' 372 | typedef typename plain_matrix_type_dense::XprKind, evaluator::Flags>::type type; | ^~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:369:45: required from 'struct Eigen::internal::generic_product_impl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Matrix, Eigen::DenseShape, Eigen::DenseShape, 7>' 369 | typedef typename nested_eval::type LhsNested; | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:486:24: required from 'static void Eigen::internal::generic_product_impl::scaleAndAddTo(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; Rhs = Eigen::Matrix; Scalar = double]' 485 | return internal::generic_product_impl | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 486 | ::scaleAndAddTo(dst_vec, a_lhs.row(0), a_rhs, alpha); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/GeneralMatrixMatrix.h:445:20: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; Rhs = Eigen::Matrix]' 445 | scaleAndAddTo(dst, lhs, rhs, Scalar(1)); | ~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >' 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:774:20: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Map, 0, Eigen::Stride<0, 0> >; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, 0, Eigen::OuterStride<> >, -1, 1, true>, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, true>, 1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 1, -1, true>, 1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, -1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1, false>, -1, -1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1, false>, -1, -1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:194:48: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Block, 1, -1, true>, 1, -1, false>; int Mode = 5; Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >; Rhs = const Eigen::Block, -1, -1, false>, -1, -1, false>; typename Dest::Scalar = double]' 194 | ::run(rhs.transpose(),lhs.transpose(), dstT, alpha); | ~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:783:113: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Map, 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/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -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/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::Map, 0, Eigen::Stride<0, 0> >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::val_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Map, 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/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose >, Eigen::Transpose > > >; _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/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:42:17: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(A) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | .transpose() | ~~~~~~~~~~~~ 39 | .lu() | ~~~~~ 40 | .solve(Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, 1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, 1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, 1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, 1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, 1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense >, 1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose >, Eigen::Transpose > > >; _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/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:42:17: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(A) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | .transpose() | ~~~~~~~~~~~~ 39 | .lu() | ~~~~~ 40 | .solve(Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 1>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 1> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 1> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 1, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 1, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 1>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:462:68: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, false>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, -1, false>, -1, -1, false>, 1, -1, false> >, const Eigen::Block, -1, 1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, -1, 1, false> >, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, 1, false> >, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, true>, 1, -1, false> >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, true>, 1, -1, false> >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, true>, 1, -1, false> >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/VectorBlock.h:56:47: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:341:54: required from 'static void Eigen::internal::trmv_selector::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose, 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/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:457:59: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; typename Dest::Scalar = double]' 457 | dst.topRows(diagSize) -= ((lhs_alpha-LhsScalar(1))*a_rhs).topRows(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false> >, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false> >, -1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false> >, -1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false> >, -1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 6; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose, -1, -1, false> >; Rhs = Eigen::Block, -1, -1, false>; typename Dest::Scalar = double]' 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::Transpose, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, const Eigen::CwiseUnaryView, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > > >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/io/deserializer.hpp:979:0: required from 'auto stan::io::deserializer::read_constrain_corr_matrix(LP&, size_t, Sizes ...) [with Ret = std::vector, -1, -1>, std::allocator, -1, -1> > >; bool Jacobian = true; LP = stan::math::var_value; Sizes = {int}; stan::require_std_vector_t* = 0; T = stan::math::var_value; size_t = long long unsigned int]' 979 | this->read_constrain_corr_matrix, Jacobian>( 980 | lp, sizes...)); stanExports_stanmarg.h:12986:0: required from 'stan::scalar_type_t model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 12984 | Psi_r_mat_1 = in__.template read_constrain_corr_matrix< 12985 | std::vector>, 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 0, Eigen::Stride<0, 0> > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose, 0, Eigen::Stride<0, 0> > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -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/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from 'void Eigen::internal::generic_dense_assignment_kernel::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator >; SrcEvaluatorTypeT = Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> > >, Eigen::CwiseUnaryOp, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 1> >; Functor = Eigen::internal::assign_op; 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/4.5/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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix, -1, -1>; T4__ = stan::math::var_value; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = stan::math::var_value; typename stan::base_type::type = stan::math::var_value; std::ostream = std::basic_ostream]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; CoeffReturnType = double; Eigen::Index = long long int]' 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> >; stan::require_dense_dynamic_t* = 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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T4__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:357:7: required from 'class Eigen::internal::redux_evaluator, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true> > >' 357 | class redux_evaluator : public internal::evaluator<_XprType> | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:414:17: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, Eigen::Matrix, 0>, 1, -1, false> >, const Eigen::Block, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 414 | ThisEvaluator thisEval(derived()); | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >, const Eigen::Product, Eigen::Matrix, 0>, Eigen::CwiseBinaryOp, const Eigen::Block, -1, 1, false>, const Eigen::CwiseNullaryOp&>(const Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix > >, 0> >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:4192:0: required from 'std::vector::type, -1, -1> > model_stanmarg_namespace::estep(const std::vector >&, const std::vector >&, const std::vector >&, const std::vector&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = double; stan::require_all_t, stan::is_stan_scalar, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, true> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, -1, 1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, -1, 1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/GeneralProduct.h:379:80: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, const Eigen::Transpose, -1, 1, true> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, const Eigen::Transpose, -1, 1, true> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, const Eigen::Transpose, -1, 1, true> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, const Eigen::Transpose, -1, 1, true> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, const Eigen::Transpose, -1, 1, true> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; Rhs = Eigen::Block, -1, 1, true>; Dest = Eigen::Block, -1, 1, true>; typename Dest::Scalar = double]' 379 | dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; Rhs = Eigen::Matrix; Dest = Eigen::Block, 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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::InnerStride<> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::InnerStride<> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::InnerStride<> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::InnerStride<> >, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 0, Eigen::Stride<0, 0> >, -1, 1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, 0, Eigen::Stride<0, 0> >, -1, 1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 23 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, 0, Eigen::Stride<0, 0> >, -1, 1, false>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:77: required from 'static void Eigen::internal::triangular_matrix_vector_product::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/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:98:7: required from 'class Eigen::PlainObjectBase >' 98 | class PlainObjectBase : public internal::dense_xpr_base::type | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:178:7: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 0>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 0>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Diagonal.h:63:53: required from 'class Eigen::Diagonal, 0>' 63 | template class Diagonal | ^~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose > >, 1, -1, false> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose > >; Rhs = Eigen::Matrix; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; CoeffReturnType = double; Eigen::Index = long long int]' 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:412:48: required from 'Eigen::DenseBase::EvalReturnType Eigen::DenseBase::eval() const [with Derived = Eigen::Product > >, Eigen::Matrix, 0>, Eigen::Transpose >, 0>; EvalReturnType = const Eigen::Matrix]' 412 | return typename internal::eval::type(derived()); | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/quad_form_sym.hpp:37:47: required from 'stan::plain_type_t stan::math::quad_form_sym(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::Transpose >; stan::require_all_eigen_t* = 0; stan::require_not_eigen_col_vector_t* = 0; stan::require_vt_same* = 0; stan::require_all_vt_arithmetic* = 0; stan::plain_type_t = Eigen::Matrix]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>, -1, 1, true>; Derived = Eigen::Block >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> >; stan::require_dense_dynamic_t* = 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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T4__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block >, 1, -1, true>, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 14 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> >; stan::require_dense_dynamic_t* = 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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T4__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, -1, 1, false> >, 1, -1, true> >, const Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, -1, 1, false> >, 1, -1, true>; U = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, -1, false>, -1, -1, false>, -1, 1, true>; Derived = Eigen::Block, -1, 1, false> >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, true>; SrcXprType = Eigen::Block, -1, 1, true>; Functor = swap_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, 1, true>; SrcXprType = Eigen::Block, -1, 1, true>; Functor = Eigen::internal::swap_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, 1, true>; Src = Eigen::Block, -1, 1, true>; Func = swap_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, 1, true>; Src = Eigen::Block, -1, 1, true>; Func = swap_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:424:22: required from 'void Eigen::DenseBase::swap(const Eigen::DenseBase&) [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, -1, 1, true>]' 424 | call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:1129:51: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/trace_inv_quad_form_ldlt.hpp:36:42: required from 'stan::return_type_t stan::math::trace_inv_quad_form_ldlt(LDLT_factor&, const EigMat2&) [with T = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; = void; stan::return_type_t = double]' 36 | return B.cwiseProduct(mdivide_left_ldlt(A, B)).sum(); | ~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_loc = Eigen::CwiseNullaryOp&>(Eigen::Matrix&, const char*, const index_multi&)::::, Eigen::Matrix >; T_covar = Eigen::Matrix; stan::return_type_t = 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 18523 | stan::math::multi_normal_lpdf( 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:60:7: required from 'class Eigen::CwiseNullaryOp, Eigen::Matrix >' 60 | class CwiseNullaryOp : public internal::dense_xpr_base< CwiseNullaryOp >::type, internal::no_assignment_operator | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:347:30: required from 'Derived& Eigen::DenseBase::setConstant(const Scalar&) [with Derived = Eigen::Matrix; Scalar = double]' 347 | return derived() = Constant(rows(), cols(), val); | ~~~~~~~~^~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseNullaryOp.h:548:10: required from 'Derived& Eigen::DenseBase::setZero() [with Derived = Eigen::Matrix]' 548 | return setConstant(Scalar(0)); | ^~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Func = sub_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Matrix >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>, -1, -1, false>]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 20 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, -1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = sub_assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>, -1, -1, true>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, -1, -1, true> >; Derived = Eigen::Block, -1, -1, false>, -1, -1, true>]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 24 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1, false>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase, -1, -1, false>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1, false> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1, false> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, -1, -1, false>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense, -1, -1, false, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 2; bool LhsIsTriangular = true; Lhs = Eigen::Matrix; Rhs = Eigen::Matrix; typename Dest::Scalar = double]' 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase >, -1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase >, -1, -1, true>, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase >, -1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase >, -1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase >, -1, -1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:329:7: required from 'class Eigen::internal::BlockImpl_dense >, -1, -1, true, true>' 329 | class BlockImpl_dense | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: [ skipping 25 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixMatrix.h:462:59: required from 'static void Eigen::internal::triangular_product_impl::run(Dest&, const Lhs&, const Rhs&, const typename Dest::Scalar&) [with Dest = Eigen::Matrix; int Mode = 1; bool LhsIsTriangular = true; Lhs = const Eigen::Transpose >; Rhs = Eigen::Matrix; typename Dest::Scalar = double]' 462 | dst.leftCols(diagSize) -= (rhs_alpha-RhsScalar(1))*a_lhs.leftCols(diagSize); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:770:14: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 0, Eigen::Stride<0, 0> >, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >, -1, 1, true>; SrcXprType = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Functor = swap_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; SrcXprType = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Functor = Eigen::internal::swap_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Src = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Func = swap_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Src = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Func = swap_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:424:22: required from 'void Eigen::DenseBase::swap(const Eigen::DenseBase&) [with OtherDerived = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>; Derived = Eigen::Block, 0, Eigen::Stride<0, 0> >, -1, 1, true>]' 424 | call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:1129:51: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/prob/multi_normal_lpdf.hpp:98:45: required from 'stan::return_type_t stan::math::multi_normal_lpdf(const T_y&, const T_loc&, const T_covar&) [with bool propto = false; T_y = std::vector, -1, 1>, std::allocator, -1, 1> > >; T_loc = Eigen::CwiseNullaryOp, -1, 1>&>(Eigen::Matrix, -1, 1>&, const char*, const index_multi&)::::, Eigen::Matrix, -1, 1> >; T_covar = Eigen::Matrix, -1, -1>; stan::return_type_t = var_value]' 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 model_stanmarg_namespace::model_stanmarg::log_prob_impl(VecR&, VecI&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; VecR = std::vector, std::allocator > >; VecI = std::vector; stan::require_vector_like_t* = 0; stan::require_vector_like_vt* = 0; stan::scalar_type_t = stan::math::var_value; std::ostream = std::basic_ostream]' 14424 | lp_accum__.add(stan::math::multi_normal_lpdf( 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&, std::vector&, std::ostream*) const [with bool propto__ = true; bool jacobian__ = true; T_ = stan::math::var_value; std::ostream = std::basic_ostream]' 22491 | return log_prob_impl(params_r, params_i, pstream); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/log_prob_grad.hpp:40:0: required from 'double stan::model::log_prob_grad(const M&, std::vector&, std::vector&, std::vector&, std::ostream*) [with bool propto = true; bool jacobian_adjust_transform = true; M = model_stanmarg_namespace::model_stanmarg; std::ostream = std::basic_ostream]' 40 | var adLogProb = model.template log_prob( 41 | ad_params_r, params_i, msgs); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1183:0: required from 'SEXPREC* rstan::stan_fit::grad_log_prob(SEXP, SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1183 | lp = stan::model::log_prob_grad(model_, par_r, par_i, gradient, &rstan::io::rcout); stanExports_stanmarg.cc:23:0: required from here 23 | .method("grad_log_prob", &rstan::stan_fit ::grad_log_prob) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, 1, -1, false>; SrcXprType = Eigen::Block, 1, -1, false>; Functor = swap_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, false>; SrcXprType = Eigen::Block, 1, -1, false>; Functor = Eigen::internal::swap_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 1, -1, false>; Src = Eigen::Block, 1, -1, false>; Func = swap_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, 1, -1, false>; Src = Eigen::Block, 1, -1, false>; Func = swap_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:424:22: required from 'void Eigen::DenseBase::swap(const Eigen::DenseBase&) [with OtherDerived = Eigen::Block, 1, -1, false>; Derived = Eigen::Block, 1, -1, false>]' 424 | call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:1033:18: [ skipping 18 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose >, Eigen::Transpose > > >; _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/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:42:17: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(A) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | .transpose() | ~~~~~~~~~~~~ 39 | .lu() | ~~~~~ 40 | .solve(Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::Transpose >; Rhs = Eigen::Matrix; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Transpose >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; CoeffReturnType = double; Eigen::Index = long long int]' 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from 'void Eigen::internal::generic_dense_assignment_kernel::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator >; SrcEvaluatorTypeT = Eigen::internal::evaluator >, Eigen::Matrix, 1> >; Functor = Eigen::internal::sub_assign_op; 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/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 17 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&; Mat2 = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Product >, Eigen::Matrix, 0> >; stan::require_dense_dynamic_t* = 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::type, T1__>::type, -1, -1> model_stanmarg_namespace::sig_inv_update(const T0__&, const std::vector&, const int&, const int&, const T4__&, std::ostream*) [with T0__ = Eigen::Matrix; T4__ = double; stan::require_all_t, stan::is_vt_not_complex, stan::is_stan_scalar >* = 0; typename boost::math::tools::promote_args::type, T1__>::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:52: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; Rhs = Eigen::Matrix; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; CoeffReturnType = double; Eigen::Index = long long int]' 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Block, 0, Eigen::OuterStride<> >, 1, -1, true>, 1, -1, false>, const Eigen::Transpose, 0, Eigen::Stride<0, 0> >, -1, 1, false> > >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:137:114: required from 'static void Eigen::internal::triangular_matrix_vector_product::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/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h:332:12: required from 'static void Eigen::internal::trmv_selector::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose, 1, -1, true>, 1, -1, false> >; int Mode = 6; typename Dest::Scalar = double]' 327 | internal::triangular_matrix_vector_product | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 328 | | ~~~~~~~~~ 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/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1043:41: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >' 1043 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: [ skipping 37 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false>, -1, 1, true>, -1, 1, false> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 35 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, 1, -1, true>, 1, -1, false> >, -1, 1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = sub_assign_op]' 780 | DstEvaluatorType dstEvaluator(dst); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>; Src = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >, -1, 1, false> >; Derived = Eigen::Block, 1, -1, true>, 1, -1, false> >, -1, 1, false>]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, false>; SrcXprType = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, -1, -1, false>; Src = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Func = sub_assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false>; Derived = Eigen::Block, -1, -1, false>]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false> >, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false> >, -1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 22 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, 1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/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, 1, -1, false>; SrcXprType = Eigen::Block >, 1, -1, false>; Functor = assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, 1, -1, false>; SrcXprType = Eigen::Block >, 1, -1, false>; Functor = Eigen::internal::assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, 1, -1, false>; Src = Eigen::Block >, 1, -1, false>; Func = assign_op]' 890 | Assignment::run(actualDst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::value), void*>::type) [with Dst = Eigen::Block, 1, -1, false>; Src = Eigen::Block >, 1, -1, false>; Func = assign_op; typename enable_if<(! evaluator_assume_aliasing::value), void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 858 | call_assignment_no_alias(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:836:18: required from 'void Eigen::internal::call_assignment(Dst&, const Src&) [with Dst = Eigen::Block, 1, -1, false>; Src = Eigen::Block >, 1, -1, false>]' 836 | call_assignment(dst, src, internal::assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Assign.h:66:28: [ skipping 19 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Matrix.h:423:29: required from 'Eigen::Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::Matrix(const Eigen::EigenBase&) [with OtherDerived = Eigen::Transpose >, Eigen::Transpose > > >; _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/4.5/StanHeaders/include/stan/math/prim/fun/mdivide_right.hpp:42:17: required from 'Eigen::Matrix::type, T1::RowsAtCompileTime, T2::ColsAtCompileTime> stan::math::mdivide_right(const EigMat1&, const EigMat2&) [with EigMat1 = Eigen::Matrix; EigMat2 = Eigen::CwiseBinaryOp, const Eigen::Map, 0, Eigen::Stride<0, 0> >, const Eigen::Matrix >; stan::require_all_eigen_t* = 0; stan::require_all_not_vt_fvar* = 0; typename stan::return_type::type = double]' 36 | return Eigen::Matrix(A) | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 38 | .transpose() | ~~~~~~~~~~~~ 39 | .lu() | ~~~~~ 40 | .solve(Eigen::Matrix(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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:606:75: required from 'const Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::CoeffReturnType Eigen::internal::product_evaluator, ProductTag, Eigen::DenseShape, Eigen::DenseShape>::coeff(Eigen::Index, Eigen::Index) const [with Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; Rhs = Eigen::Matrix; int ProductTag = 8; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; CoeffReturnType = double; Eigen::Index = long long int]' 606 | return (m_lhs.row(row).transpose().cwiseProduct( m_rhs.col(col) )).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:654:63: required from 'void Eigen::internal::generic_dense_assignment_kernel::assignCoeff(Eigen::Index, Eigen::Index) [with DstEvaluatorTypeT = Eigen::internal::evaluator >; SrcEvaluatorTypeT = Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 1> >; Functor = Eigen::internal::assign_op; 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/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:668:16: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/model/indexing/assign.hpp:60:0: required from 'void stan::model::assign(T&&, U&&, const char*) [with T = Eigen::Matrix&; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Product >, Eigen::Matrix, 0> > >; stan::require_t::type&, typename std::decay<_Tp2>::type> >* = 0; stan::require_all_not_t, internal::is_tuple >* = 0]' 60 | internal::assign_impl(x, std::forward(y), name); stanExports_stanmarg.h:3413:0: required from 'Eigen::Matrix::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type, -1, 1> model_stanmarg_namespace::twolevel_logdens(const std::vector >&, const std::vector >&, const T2__&, const std::vector >&, const std::vector&, const std::vector&, const std::vector&, const int&, const std::vector&, const T9__&, const T10__&, const T11__&, const T12__&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const std::vector&, const int&, const int&, const int&, const int&, std::ostream*) [with T0__ = double; T1__ = double; T2__ = Eigen::Matrix; T3__ = double; T9__ = Eigen::Matrix; T10__ = Eigen::Matrix; T11__ = Eigen::Matrix; T12__ = Eigen::Matrix; stan::require_all_t, stan::is_stan_scalar, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_stan_scalar, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex, stan::is_col_vector, stan::is_vt_not_complex, stan::is_eigen_matrix_dynamic, stan::is_vt_not_complex >* = 0; typename boost::math::tools::promote_args::type, T3__, typename stan::base_type::type, typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename boost::math::tools::promote_args::type, typename stan::base_type::type, typename stan::base_type::type>::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; typename stan::base_type::type = double; std::ostream = std::basic_ostream]' 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 >; VecR = std::vector; VecI = std::vector; VecVar = std::vector; stan::require_vector_like_vt* = 0; stan::require_vector_like_vt* = 0; stan::require_vector_vt* = 0; std::ostream = std::basic_ostream]' 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&, std::vector&, std::vector&, bool, bool, std::ostream*) const [with RNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; std::ostream = std::basic_ostream]' 22480 | write_array_impl(base_rng, params_r, params_i, vars, 22481 | emit_transformed_parameters, emit_generated_quantities, pstream); D:/RCompile/CRANpkg/lib/4.5/rstan/include/rstan/stan_fit.hpp:1105:0: required from 'SEXPREC* rstan::stan_fit::constrain_pars(SEXP) [with Model = model_stanmarg_namespace::model_stanmarg; RNG_t = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >; SEXP = SEXPREC*]' 1105 | model_.write_array(base_rng, params_r, params_i, par); stanExports_stanmarg.cc:26:0: required from here 26 | .method("constrain_pars", &rstan::stan_fit ::constrain_pars) D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, -1, -1, false> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, -1, -1, false> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, -1, false> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator >, -1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator >, -1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:78: required from 'struct Eigen::internal::binary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> > >' 722 | struct evaluator > | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >; Functor = sub_assign_op]' 774 | SrcEvaluatorType srcEvaluator(src); | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:954:31: required from 'static void Eigen::internal::Assignment::run(DstXprType&, const SrcXprType&, const Functor&) [with DstXprType = Eigen::Block, -1, -1, true>; SrcXprType = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block >, -1, -1, true> >; Functor = Eigen::internal::sub_assign_op; Weak = void]' 954 | call_dense_assignment_loop(dst, src, func); | ~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:890:49: [ skipping 26 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/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&) [with OtherDerived = Eigen::HouseholderSequence, Eigen::Matrix, 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/4.5/RcppEigen/include/Eigen/src/Eigenvalues/Tridiagonalization.h:453:11: required from 'static void Eigen::internal::tridiagonalization_inplace_selector::run(MatrixType&, DiagonalType&, SubDiagonalType&, CoeffVectorType&, bool) [with DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; MatrixType = Eigen::Matrix; int Size = -1; bool IsComplex = false; CoeffVectorType = Eigen::Matrix]' 453 | mat = HouseholderSequenceType(mat, hCoeffs.conjugate()) | ~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 454 | .setLength(mat.rows() - 1) | ~~~~~~~~~~~~~~~~~~~~~~~~~~ 455 | .setShift(1); | ~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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; DiagonalType = Eigen::Matrix; SubDiagonalType = Eigen::Matrix; CoeffVectorType = Eigen::Matrix]' 434 | tridiagonalization_inplace_selector::run(mat, diag, subdiag, hcoeffs, extractQ); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:458:39: required from 'Eigen::SelfAdjointEigenSolver& Eigen::SelfAdjointEigenSolver<_MatrixType>::compute(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 458 | internal::tridiagonalization_inplace(mat, diag, m_subdiag, m_hcoeffs, computeEigenvectors); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h:181:14: required from 'Eigen::SelfAdjointEigenSolver<_MatrixType>::SelfAdjointEigenSolver(const Eigen::EigenBase&, int) [with InputType = Eigen::Matrix; _MatrixType = Eigen::Matrix]' 181 | compute(matrix.derived(), options); | ~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/optimization/newton.hpp:19:0: required from here 19 | Eigen::SelfAdjointEigenSolver solver(H); D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> >, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, 1, 0, -1, 1>, 0, Eigen::Stride<0, 0> > >' 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from 'void stan::math::internal::callback_vari::chain() [with T = double; F = stan::math::sum > >(const std::vector, arena_allocator > >&)::]' 21 | inline void chain() final { rev_functor_(*this); } D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayBase.h:39:34: required from 'class Eigen::ArrayBase, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> > >' 39 | template class ArrayBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ArrayWrapper.h:42:7: required from 'class Eigen::ArrayWrapper, -1, -1>, 0, Eigen::Stride<0, 0> > >::adj_Op, Eigen::Map, -1, -1>, 0, Eigen::Stride<0, 0> > >, 0> >' 42 | class ArrayWrapper : public ArrayBase > | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: recursively required from 'void stan::math::internal::callback_vari::chain() [with T = double; F = stan::math::trace, -1, -1> >(const Eigen::Matrix, -1, -1>&)::]' 21 | inline void chain() final { rev_functor_(*this); } D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/core/callback_vari.hpp:21:0: required from here D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, Eigen::Transpose >, 0, 8>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:66:0: required from 'void stan::math::internal::mdivide_left_spd_vv_vari::chain() [with int R1 = -1; int C1 = -1; int R2 = -1; int C2 = -1]' 66 | -= adjB * alloc_->C_.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:62:0: required from here 62 | virtual void chain() { D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1> >::adj_Op, Eigen::Matrix, -1, -1> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, -1, -1> >::adj_Op, Eigen::Matrix, -1, -1> >, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, -1, -1> >::adj_Op, Eigen::Matrix, -1, -1> >, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1> >::adj_Op, Eigen::Matrix, -1, -1> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1> >::adj_Op, Eigen::Matrix, -1, -1> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:103:7: required from 'class Eigen::CwiseUnaryViewImpl, -1, -1> >::adj_Op, Eigen::Matrix, -1, -1>, Eigen::Dense>' 103 | class CwiseUnaryViewImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryView.h:58:7: required from 'class Eigen::CwiseUnaryView, -1, -1> >::adj_Op, Eigen::Matrix, -1, -1> >' 58 | class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> | ^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:89:0: required from 'void stan::math::internal::quad_form_vari::chain() [with Ta = stan::math::var_value; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = -1]' 89 | matrix_d adjC = impl_->C_.adj(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, -1, -1>&>(Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, -1, -1>&>(Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, -1, -1>&>(Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:94:7: required from 'class Eigen::CwiseUnaryOpImpl, -1, -1>&>(Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1>, Eigen::Dense>' 94 | class CwiseUnaryOpImpl | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseUnaryOp.h:55:7: required from 'class Eigen::CwiseUnaryOp, -1, -1>&>(Eigen::Matrix, -1, -1>&)::::, const Eigen::Matrix, -1, -1> >' 55 | class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, internal::no_assignment_operator | ^~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:75:27: required from 'stan::math::value_of, -1, -1>&>(Eigen::Matrix, -1, -1>&):: [with auto:11 = Eigen::Matrix, -1, -1>]' 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/meta/holder.hpp:370:41: required by substitution of 'template()((declval)()...))>* > auto stan::math::make_holder(const F&, Args&& ...) [with F = stan::math::value_of, -1, -1>&>(Eigen::Matrix, -1, -1>&)::; Args = {Eigen::Matrix, -1, -1, 0, -1, -1>&}; stan::require_plain_type_t()((declval)()...))>* = ]' 370 | decltype(std::declval()(std::declval()...))>* = nullptr> | ~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/prim/fun/value_of.hpp:73:21: required from 'auto stan::math::value_of(EigMat&&) [with EigMat = Eigen::Matrix, -1, -1>&; stan::require_eigen_dense_base_t* = 0; stan::require_not_st_arithmetic* = 0]' 73 | return make_holder( | ~~~~~~~~~~~^ 74 | [](auto& a) { | ~~~~~~~~~~~~~ 75 | return a.unaryExpr([](const auto& scal) { return value_of(scal); }); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 76 | }, | ~~ 77 | std::forward(M)); | ~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from 'void stan::math::internal::quad_form_vari::chain() [with Ta = stan::math::var_value; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = -1]' 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from 'void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = stan::math::var_value; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = -1]' 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from 'void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = stan::math::var_value; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = -1]' 78 | chainB(B, Ad, Bd, adjC); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from 'void stan::math::internal::quad_form_vari::chain() [with Ta = stan::math::var_value; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = -1]' 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:37:44: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; bool NeedToTranspose = false; ResScalar = double]' 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from 'double stan::mcmc::diag_e_metric::T(stan::mcmc::diag_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]' 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:39: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]' 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]' 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]' 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:54: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]' 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]' 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]' 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix > >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:37:51: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Matrix; U = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; bool NeedToTranspose = false; ResScalar = double]' 37 | return a.template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Matrix, const Eigen::Matrix >; Derived = Eigen::Matrix; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/diag_e_metric.hpp:21:0: required from 'double stan::mcmc::diag_e_metric::T(stan::mcmc::diag_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]' 21 | return 0.5 * z.p.dot(z.inv_e_metric_.cwiseProduct(z.p)); D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0> >, const Eigen::Matrix >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]' 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]' 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]' 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Block >, -1, 1, false>, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Block >, -1, 1, false>, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Block >, -1, 1, false>, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, const Eigen::Block >, -1, 1, false>, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, const Eigen::Block >, -1, 1, false>, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, const Eigen::Block >, -1, 1, false>, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from 'void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]' 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >; Src = Eigen::Product, Eigen::Transpose >, 0>; Func = sub_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 850 | typename plain_matrix_type::type tmp(src); | ^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:66:0: required from 'void stan::math::internal::mdivide_left_spd_vv_vari::chain() [with int R1 = -1; int C1 = -1; int R2 = -1; int C2 = -1]' 65 | Eigen::Map(variRefA_, M_, M_).adj() 66 | -= adjB * alloc_->C_.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:62:0: required from here 62 | virtual void chain() { D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, false>, Eigen::Transpose >, 0>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, false>, Eigen::Transpose >, 0> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, false>, Eigen::Transpose >, 0> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:120:7: required from 'class Eigen::internal::dense_product_base, 1, -1, false>, Eigen::Transpose >, 0, 7>' 120 | class dense_product_base | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:152:7: required from 'class Eigen::ProductImpl, 1, -1, false>, Eigen::Transpose >, 0, Eigen::Dense>' 152 | class ProductImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:71:7: required from 'class Eigen::Product, 1, -1, false>, Eigen::Transpose >, 0>' 71 | class Product : public ProductImpl<_Lhs,_Rhs,Option, | ^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:345:45: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from 'void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]' 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >; Src = Eigen::Product, Eigen::Transpose >, 0>; Func = sub_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 850 | typename plain_matrix_type::type tmp(src); | ^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:66:0: required from 'void stan::math::internal::mdivide_left_spd_vv_vari::chain() [with int R1 = -1; int C1 = -1; int R2 = -1; int C2 = -1]' 65 | Eigen::Map(variRefA_, M_, M_).adj() 66 | -= adjB * alloc_->C_.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:62:0: required from here 62 | virtual void chain() { D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false> >, const Eigen::Block >, -1, 1, false>, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>; U = Eigen::Block >, -1, 1, false>, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from 'void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]' 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >; Src = Eigen::Product, Eigen::Transpose >, 0>; Func = sub_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 850 | typename plain_matrix_type::type tmp(src); | ^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:66:0: required from 'void stan::math::internal::mdivide_left_spd_vv_vari::chain() [with int R1 = -1; int C1 = -1; int R2 = -1; int C2 = -1]' 65 | Eigen::Map(variRefA_, M_, M_).adj() 66 | -= adjB * alloc_->C_.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:62:0: required from here 62 | virtual void chain() { D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, 1, -1, false>, 1, -1, true> >, const Eigen::Block >, -1, 1, false> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, 1, -1, false>, 1, -1, true>; U = Eigen::Block >, -1, 1, false>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 7 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/PlainObjectBase.h:883:25: required from 'void Eigen::PlainObjectBase::_init1(const Eigen::DenseBase&) [with T = Eigen::Product, Eigen::Transpose >, 0>; OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::Matrix]' 883 | this->_set_noalias(other); | ~~~~~~~~~~~~~~~~~~^~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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::Transpose >, 0>; _Scalar = double; int _Rows = -1; int _Cols = -1; int _Options = 0; int _MaxRows = -1; int _MaxCols = -1]' 332 | Base::template _init1(x); | ~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >; Src = Eigen::Product, Eigen::Transpose >, 0>; Func = sub_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 850 | typename plain_matrix_type::type tmp(src); | ^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:164:18: required from 'Derived& Eigen::MatrixBase::operator-=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::Product, Eigen::Transpose >, 0>; Derived = Eigen::CwiseUnaryView*, -1, -1> > >::adj_Op, Eigen::Map*, -1, -1> > >]' 164 | call_assignment(derived(), other.derived(), internal::sub_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:66:0: required from 'void stan::math::internal::mdivide_left_spd_vv_vari::chain() [with int R1 = -1; int C1 = -1; int R2 = -1; int C2 = -1]' 65 | Eigen::Map(variRefA_, M_, M_).adj() 66 | -= adjB * alloc_->C_.transpose(); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/mdivide_left_spd.hpp:62:0: required from here 62 | virtual void chain() { D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, 1, -1, true> >, -1, 1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:302:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true> >, -1, 1, true>, 1>' 302 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:555:7: required from 'class Eigen::DenseCoeffsBase, 1, -1, true> >, -1, 1, true>, 3>' 555 | class DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, 1, -1, true> >, -1, 1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, 1, -1, true> >, -1, 1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:37:34: required from 'class Eigen::MapBase, 1, -1, true> >, -1, 1, true>, 0>' 37 | template class MapBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MapBase.h:223:34: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/AssignEvaluator.h:850:41: required from 'void Eigen::internal::call_assignment(Dst&, const Src&, const Func&, typename enable_if::value, void*>::type) [with Dst = Eigen::CwiseUnaryView, -1, -1> >::adj_Op, Eigen::Matrix, -1, -1> >; Src = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Func = add_assign_op; typename enable_if::value, void*>::type = void*; typename evaluator_traits::Shape = Eigen::DenseShape]' 850 | typename plain_matrix_type::type tmp(src); | ^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:177:18: required from 'Derived& Eigen::MatrixBase::operator+=(const Eigen::MatrixBase&) [with OtherDerived = Eigen::CwiseBinaryOp, const Eigen::Product, Eigen::Matrix, 0>, Eigen::Transpose >, 0>, const Eigen::Product >, Eigen::Matrix, 0>, Eigen::Matrix, 0> >; Derived = Eigen::CwiseUnaryView, -1, -1> >::adj_Op, Eigen::Matrix, -1, -1> >]' 177 | call_assignment(derived(), other.derived(), internal::add_assign_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:69:0: required from 'void stan::math::internal::quad_form_vari::chainB(Eigen::Matrix, Rb, Cb>&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = stan::math::var_value; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = -1]' 69 | B.adj() += Ad * Bd * adjC.transpose() + Ad.transpose() * Bd * adjC; D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:78:0: required from 'void stan::math::internal::quad_form_vari::chainAB(Eigen::Matrix&, Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&, const Eigen::Matrix&) [with Ta = stan::math::var_value; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = -1]' 78 | chainB(B, Ad, Bd, adjC); D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:91:0: required from 'void stan::math::internal::quad_form_vari::chain() [with Ta = stan::math::var_value; int Ra = -1; int Ca = -1; Tb = stan::math::var_value; int Rb = -1; int Cb = -1]' 91 | chainAB(impl_->A_, impl_->B_, value_of(impl_->A_), value_of(impl_->B_), D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/stan/math/rev/fun/quad_form.hpp:88:0: required from here 88 | virtual void chain() { D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:172:103: required from 'class Eigen::internal::BlockImpl_dense, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true, false>' 172 | template class BlockImpl_dense | ^~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:154:7: required from 'class Eigen::BlockImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true, Eigen::Dense>' 154 | class BlockImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Block.h:103:81: required from 'class Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>' 103 | template class Block | ^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:43: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]' 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]' 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]' 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >; Rhs = Eigen::Matrix; Dest = Eigen::Matrix; int StorageOrder = 0; bool BlasCompatible = true; typename Dest::Scalar = double]' 207 | ::run(rhs.transpose(), lhs.transpose(), destT, alpha); | ~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:388:34: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]' 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]' 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]' 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:23: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]' 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]' 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]' 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:148:7: required from 'class Eigen::CwiseBinaryOpImpl, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true>, Eigen::Dense>' 148 | class CwiseBinaryOpImpl | ^~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CwiseBinaryOp.h:77:7: required from 'class Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >' 77 | class CwiseBinaryOp : | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:56: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: [ skipping 16 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]' 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]' 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]' 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'class Eigen::DenseCoeffsBase > >, 0>': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:481:7: required from 'class Eigen::DenseCoeffsBase > >, 2>' 481 | class DenseCoeffsBase : public DenseCoeffsBase | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseBase.h:41:34: required from 'class Eigen::DenseBase > > >' 41 | template class DenseBase | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/MatrixBase.h:48:34: required from 'class Eigen::MatrixBase > > >' 48 | template class MatrixBase | ^~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:118:37: required from 'class Eigen::TransposeImpl >, Eigen::Dense>' 118 | template class TransposeImpl | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Transpose.h:52:37: required from 'class Eigen::Transpose > >' 52 | template class Transpose | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]' 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]' 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]' 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:56:30: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 56 | >::type PacketReturnType; | ^~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h: In instantiation of 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:311:41: required from 'struct Eigen::internal::unary_evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, Eigen::internal::IndexBased, double>' 311 | CoeffReadCost = evaluator::CoeffReadCost, | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:90:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >' 90 | struct evaluator : public unary_evaluator | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:100:8: required from 'struct Eigen::internal::evaluator, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> > >' 100 | struct evaluator | ^~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:739:41: required from 'struct Eigen::internal::binary_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >, Eigen::internal::IndexBased, Eigen::internal::IndexBased, double, double>' 739 | CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), | ^~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:722:8: [ skipping 21 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]' 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]' 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]' 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/CoreEvaluators.h:1071:54: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 1071 | PacketAlignment = unpacket_traits::alignment, | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h: In instantiation of 'Eigen::Index Eigen::internal::first_default_aligned(const Eigen::DenseBase&) [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Eigen::Index = long long int]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:243:63: required from 'static Eigen::internal::redux_impl::Scalar Eigen::internal::redux_impl::run(const Evaluator&, const Func&, const XprType&) [with XprType = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; Func = Eigen::internal::scalar_sum_op; Evaluator = Eigen::internal::redux_evaluator, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> > >; Scalar = double]' 243 | const Index alignedStart = internal::first_default_aligned(xpr); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:418:56: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::redux(const Func&) const [with BinaryOp = Eigen::internal::scalar_sum_op; Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 418 | return internal::redux_impl::run(thisEval, func, derived()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Redux.h:463:25: required from 'typename Eigen::internal::traits::Scalar Eigen::DenseBase::sum() const [with Derived = Eigen::CwiseBinaryOp, const Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true> >, const Eigen::Block, -1, 1, true> >; typename Eigen::internal::traits::Scalar = double]' 463 | return derived().redux(Eigen::internal::scalar_sum_op()); | ~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:50:63: required from 'static Eigen::internal::dot_nocheck::ResScalar Eigen::internal::dot_nocheck::run(const Eigen::MatrixBase&, const Eigen::MatrixBase&) [with T = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; U = Eigen::Block, -1, 1, true>; ResScalar = double]' 50 | return a.transpose().template binaryExpr(b).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Dot.h:84:58: required from 'typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType Eigen::MatrixBase::dot(const Eigen::MatrixBase&) const [with OtherDerived = Eigen::Block, -1, 1, true>; Derived = Eigen::Block, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, 1, -1, true>; typename Eigen::ScalarBinaryOpTraits::Scalar, typename Eigen::internal::traits::Scalar>::ReturnType = double; typename Eigen::internal::traits::Scalar = double; typename Eigen::internal::traits::Scalar = double]' 84 | return internal::dot_nocheck::run(*this, other); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:380:62: [ skipping 15 instantiation contexts, use -ftemplate-backtrace-limit=0 to disable ] D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:251:64: required from 'static void Eigen::internal::generic_product_impl::evalTo(Dst&, const Lhs&, const Rhs&) [with Dst = Eigen::Matrix; Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix]' 251 | dst.coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:124:75: required from 'Eigen::internal::product_evaluator, ProductTag, LhsShape, RhsShape>::product_evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; int ProductTag = 6; LhsShape = Eigen::DenseShape; RhsShape = Eigen::DenseShape; typename Eigen::internal::traits::Lhs>::Scalar = double; typename Eigen::Product::Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; typename Eigen::internal::traits::Rhs>::Scalar = double; typename Eigen::Product::Rhs = Eigen::Matrix; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 124 | generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); | ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/ProductEvaluators.h:35:90: required from 'Eigen::internal::evaluator >::evaluator(const XprType&) [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Options = 0; XprType = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>, Eigen::Matrix, 0>]' 35 | EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} | ^ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/Product.h:137:22: required from 'Eigen::internal::dense_product_base::operator const Scalar() const [with Lhs = Eigen::Product, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose > >, Eigen::Matrix, 0>; Rhs = Eigen::Matrix; int Option = 0; Scalar = double]' 137 | return internal::evaluator(derived()).coeff(0,0); | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/StanHeaders/include/src/stan/mcmc/hmc/hamiltonians/dense_e_metric.hpp:22:0: required from 'double stan::mcmc::dense_e_metric::T(stan::mcmc::dense_e_point&) [with Model = model_stanmarg_namespace::model_stanmarg; BaseRNG = boost::random::additive_combine_engine, boost::random::linear_congruential_engine >]' 22 | return 0.5 * z.p.transpose() * z.inv_e_metric_ * z.p; D:/RCompile/CRANpkg/lib/4.5/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/4.5/RcppEigen/include/Eigen/src/Core/DenseCoeffsBase.h:654:74: warning: ignoring attributes on template argument 'Eigen::internal::packet_traits::type' {aka '__m128d'} [-Wignored-attributes] 654 | return internal::first_aligned::alignment),Derived>(m); | ^~~~~~~~~ D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h: In function 'static void Eigen::internal::selfadjoint_product_impl::run(Dest&, const Lhs&, const Rhs&, const Scalar&) [with Dest = Eigen::Block, -1, 1, false>; Lhs = Eigen::Block, -1, -1, false>; int LhsMode = 17; Rhs = Eigen::CwiseBinaryOp, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Block, -1, 1, true>, -1, 1, false> >]': D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/SelfadjointMatrixVector.h:229:7: warning: 'result' may be used uninitialized [-Wmaybe-uninitialized] 227 | internal::selfadjoint_matrix_vector_product::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/4.5/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::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::run( | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In file included from D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/Core:341: D:/RCompile/CRANpkg/lib/4.5/RcppEigen/include/Eigen/src/Core/products/TriangularMatrixVector.h: In function 'static void Eigen::internal::trmv_selector::run(const Lhs&, const Rhs&, Dest&, const typename Dest::Scalar&) [with Lhs = Eigen::Transpose, -1, -1, false>, -1, -1, false> >; Rhs = Eigen::Transpose, const Eigen::CwiseNullaryOp, const Eigen::Matrix >, const Eigen::Transpose, -1, -1, false>, -1, 1, true>, -1, 1, false> > > >; Dest = Eigen::Transpose, 1, -1, true>, 1, -1, false> >; int Mode = 6]': D:/RCompile/CRANpkg/lib/4.5/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 | | ~~~~~~~~~ 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/4.5/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::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 | ^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ g++ -shared -s -static-libgcc -o blavaan.dll tmp.def RcppExports.o stanExports_stanmarg.o -LD:/RCompile/CRANpkg/lib/4.5/RcppParallel/libs/x64 -lRcppParallel -LD:/RCompile/CRANpkg/lib/4.5/RcppParallel/lib/x64 -ltbb -ltbbmalloc -LD:/RCompile/CRANpkg/lib/4.5/RcppParallel/lib/x64 -Wl,-rpath,D:/RCompile/CRANpkg/lib/4.5/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-4.5.1/bin/x64 -lR make[1]: Leaving directory '/d/temp/2025_07_19_01_50_00_654/RtmpUTYrc8/R.INSTALL1a7b45f1514b6/blavaan/src' make[1]: Entering directory '/d/temp/2025_07_19_01_50_00_654/RtmpUTYrc8/R.INSTALL1a7b45f1514b6/blavaan/src' make[1]: Leaving directory '/d/temp/2025_07_19_01_50_00_654/RtmpUTYrc8/R.INSTALL1a7b45f1514b6/blavaan/src' installing to d:/Rcompile/CRANpkg/lib/4.5/00LOCK-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)