• using R version 4.6.0 Patched (2026-05-01 r89994)
  • using platform: aarch64-apple-darwin23
  • R was compiled by     Apple clang version 17.0.0 (clang-1700.3.19.1)     GNU Fortran (GCC) 14.2.0
  • running under: macOS Sequoia 15.7.1
  • using session charset: UTF-8 * current time: 2026-05-05 07:08:12 UTC
  • checking for file ‘ccar3/DESCRIPTION’ ... OK
  • this is package ‘ccar3’ version ‘0.1.1’
  • package encoding: UTF-8
  • checking package namespace information ... OK
  • checking package dependencies ... OK
  • checking if this is a source package ... OK
  • checking if there is a namespace ... OK
  • checking for executable files ... OK
  • checking for hidden files and directories ... OK
  • checking for portable file names ... OK
  • checking for sufficient/correct file permissions ... OK
  • checking whether package ‘ccar3’ can be installed ... [2s/2s] OK See the install log for details.
  • checking installed package size ... OK
  • checking package directory ... OK
  • checking DESCRIPTION meta-information ... OK
  • checking top-level files ... OK
  • checking for left-over files ... OK
  • checking index information ... OK
  • checking package subdirectories ... OK
  • checking code files for non-ASCII characters ... OK
  • checking R files for syntax errors ... OK
  • checking whether the package can be loaded ... [0s/0s] OK
  • checking whether the package can be loaded with stated dependencies ... [0s/0s] OK
  • checking whether the package can be unloaded cleanly ... [0s/0s] OK
  • checking whether the namespace can be loaded with stated dependencies ... [0s/0s] OK
  • checking whether the namespace can be unloaded cleanly ... [0s/0s] OK
  • checking loading without being on the library search path ... [0s/0s] OK
  • checking dependencies in R code ... OK
  • checking S3 generic/method consistency ... OK
  • checking replacement functions ... OK
  • checking foreign function calls ... OK
  • checking R code for possible problems ... [2s/3s] OK
  • checking Rd files ... [0s/0s] OK
  • checking Rd metadata ... OK
  • checking Rd cross-references ... OK
  • checking for missing documentation entries ... OK
  • checking for code/documentation mismatches ... OK
  • checking Rd \usage sections ... OK
  • checking Rd contents ... OK
  • checking for unstated dependencies in examples ... OK
  • checking examples ... [0s/0s] OK
  • checking for unstated dependencies in ‘tests’ ... OK
  • checking tests ... [26s/36s] ERROR   Running ‘testthat.R’ [26s/36s] Running the tests in ‘tests/testthat.R’ failed. Complete output:   > # This file is part of the standard setup for testthat.   > # It is recommended that you do not modify it.   > #   > # Where should you do additional test configuration?   > # Learn more about the roles of various files in:   > # * https://r-pkgs.org/testing-design.html#sec-tests-files-overview   > # * https://testthat.r-lib.org/articles/special-files.html   >   > library(testthat)   > library(ccar3)   >   > test_check("ccar3")       Permutation 1 out of 50 123456789    Permutation 2 out of 50 123456789    Permutation 3 out of 50 123456789    Permutation 4 out of 50 123456789    Permutation 5 out of 50 123456789    Permutation 6 out of 50 123456789    Permutation 7 out of 50 123456789    Permutation 8 out of 50 123456789    Permutation 9 out of 50 123456789    Permutation 10 out of 50 123456789    Permutation 11 out of 50 123456789    Permutation 12 out of 50 123456789    Permutation 13 out of 50 123456789    Permutation 14 out of 50 123456789    Permutation 15 out of 50 123456789    Permutation 16 out of 50 123456789    Permutation 17 out of 50 123456789    Permutation 18 out of 50 123456789    Permutation 19 out of 50 123456789    Permutation 20 out of 50 123456789    Permutation 21 out of 50 123456789    Permutation 22 out of 50 123456789    Permutation 23 out of 50 123456789    Permutation 24 out of 50 123456789    Permutation 25 out of 50 123456789    Permutation 26 out of 50 123456789    Permutation 27 out of 50 123456789    Permutation 28 out of 50 123456789    Permutation 29 out of 50 123456789    Permutation 30 out of 50 123456789    Permutation 31 out of 50 123456789    Permutation 32 out of 50 123456789    Permutation 33 out of 50 123456789    Permutation 34 out of 50 123456789    Permutation 35 out of 50 123456789    Permutation 36 out of 50 123456789    Permutation 37 out of 50 123456789    Permutation 38 out of 50 123456789    Permutation 39 out of 50 123456789    Permutation 40 out of 50 123456789    Permutation 41 out of 50 123456789    Permutation 42 out of 50 123456789    Permutation 43 out of 50 123456789    Permutation 44 out of 50 123456789    Permutation 45 out of 50 123456789    Permutation 46 out of 50 123456789    Permutation 47 out of 50 123456789    Permutation 48 out of 50 123456789    Permutation 49 out of 50 123456789    Permutation 50 out of 50 123456789   Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0479      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0479      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0714      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0714      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0714      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0711      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0802      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0613      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0479      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0374      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.0479      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635      Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635      Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635      Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635      Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635      Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635      Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635      Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635      Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635      Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2331      Estimating optimal shrinkage intensity lambda.var (variance vector): 1      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1635      Estimating optimal shrinkage intensity lambda.var (variance vector): 0.3507      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.2029      Estimating optimal shrinkage intensity lambda.var (variance vector): 0.8132      Estimating optimal shrinkage intensity lambda (correlation matrix): 0.1408      Saving _problems/test-cca_group_rrr-79.R   [1] "Done ADMM"   [1] "Done CVXR"   [1] "We have:"   [1] 100 1 5   [1] "--------------------------------------"   [1] "Generating data ..."   [1] "Number of non zeros is: 5"   [1] "Data generated."   [1] "--------------------------------------"   eps = 1e-04 maxiter = 500      iter: 50 r: 8.41e-15 s: 0.0386   iter: 100 r: 8.12e-15 s: 0.0131   iter: 150 r: 8.55e-15 s: 0.00634   iter: 200 r: 8.43e-15 s: 0.00357   iter: 250 r: 8.62e-15 s: 0.00221   iter: 300 r: 8.77e-15 s: 0.00145   iter: 350 r: 8.94e-15 s: 0.000977   iter: 400 r: 8.72e-15 s: 0.000672   iter: 450 r: 8.5e-15 s: 0.000466   iter: 500 r: 9.08e-15 s: 0.000324   ADMM did not converge (hit maxiter).   [1] "We have:"   [1] 100 1 5   [1] "--------------------------------------"   [1] "Generating data ..."   [1] "Number of non zeros is: 5"   [1] "Data generated."   [1] "--------------------------------------"   eps = 1e-04 maxiter = 500      ADMM converged.   [1] "We have:"   [1] 100 1 5   [1] "--------------------------------------"   [1] "Generating data ..."   [1] "Number of non zeros is: 5"   [1] "Data generated."   [1] "--------------------------------------"      Starting lambda 1/7: 0.5    lambda 1/7 = 0.5   Finished lambda 1/7 in 0.0s   Starting lambda 2/7: 0.1    lambda 2/7 = 0.1   Finished lambda 2/7 in 0.0s   Starting lambda 3/7: 0.075    lambda 3/7 = 0.075   Finished lambda 3/7 in 0.0s   Starting lambda 4/7: 0.05    lambda 4/7 = 0.05   Finished lambda 4/7 in 0.0s   Starting lambda 5/7: 0.01    lambda 5/7 = 0.01   Finished lambda 5/7 in 0.0s   Starting lambda 6/7: 0.001    lambda 6/7 = 0.001   Finished lambda 6/7 in 0.0s   Starting lambda 7/7: 0.0001    lambda 7/7 = 0.0001   Finished lambda 7/7 in 0.0s   Starting lambda 1/7: 0.5    lambda 1/7 = 0.5   Finished lambda 1/7 in 0.0s   Starting lambda 2/7: 0.1    lambda 2/7 = 0.1   Finished lambda 2/7 in 0.0s   Starting lambda 3/7: 0.075    lambda 3/7 = 0.075   Finished lambda 3/7 in 0.0s   Starting lambda 4/7: 0.05    lambda 4/7 = 0.05   Finished lambda 4/7 in 0.0s   Starting lambda 5/7: 0.01    lambda 5/7 = 0.01   Finished lambda 5/7 in 0.0s   Starting lambda 6/7: 0.001    lambda 6/7 = 0.001   Finished lambda 6/7 in 0.0s   Starting lambda 7/7: 0.0001    lambda 7/7 = 0.0001   Finished lambda 7/7 in 0.0s   Starting lambda 1/7: 0.5    lambda 1/7 = 0.5   Finished lambda 1/7 in 0.0s   Starting lambda 2/7: 0.1    lambda 2/7 = 0.1   Finished lambda 2/7 in 0.0s   Starting lambda 3/7: 0.075    lambda 3/7 = 0.075   Finished lambda 3/7 in 0.0s   Starting lambda 4/7: 0.05    lambda 4/7 = 0.05   Finished lambda 4/7 in 0.0s   Starting lambda 5/7: 0.01    lambda 5/7 = 0.01   Finished lambda 5/7 in 0.0s   Starting lambda 6/7: 0.001    lambda 6/7 = 0.001   Finished lambda 6/7 in 0.0s   Starting lambda 7/7: 0.0001    lambda 7/7 = 0.0001   Finished lambda 7/7 in 0.0s   Starting lambda 1/7: 0.5    lambda 1/7 = 0.5   Finished lambda 1/7 in 0.0s   Starting lambda 2/7: 0.1    lambda 2/7 = 0.1   Finished lambda 2/7 in 0.0s   Starting lambda 3/7: 0.075    lambda 3/7 = 0.075   Finished lambda 3/7 in 0.0s   Starting lambda 4/7: 0.05    lambda 4/7 = 0.05   Finished lambda 4/7 in 0.0s   Starting lambda 5/7: 0.01    lambda 5/7 = 0.01   Finished lambda 5/7 in 0.0s   Starting lambda 6/7: 0.001    lambda 6/7 = 0.001   Finished lambda 6/7 in 0.0s   Starting lambda 7/7: 0.0001    lambda 7/7 = 0.0001   Finished lambda 7/7 in 0.0s   Starting lambda 1/7: 0.5    lambda 1/7 = 0.5   Finished lambda 1/7 in 0.0s   Starting lambda 2/7: 0.1    lambda 2/7 = 0.1   Finished lambda 2/7 in 0.0s   Starting lambda 3/7: 0.075    lambda 3/7 = 0.075   Finished lambda 3/7 in 0.0s   Starting lambda 4/7: 0.05    lambda 4/7 = 0.05   Finished lambda 4/7 in 0.0s   Starting lambda 5/7: 0.01    lambda 5/7 = 0.01   Finished lambda 5/7 in 0.0s   Starting lambda 6/7: 0.001    lambda 6/7 = 0.001   Finished lambda 6/7 in 0.0s   Starting lambda 7/7: 0.0001    lambda 7/7 = 0.0001   Finished lambda 7/7 in 0.0s   Refitting at selected lambda with ADMM logs...      Starting lambda 1/1: 0.05    lambda 1/1 = 0.05      iter 1 r=0.938376 s=0.402581      iter 2 r=0.386388 s=0.351783      iter 3 r=0.174349 s=0.213626      iter 4 r=0.0894817 s=0.118771      iter 5 r=0.0499279 s=0.0651281      iter 6 r=0.0292555 s=0.0362484      iter 7 r=0.017375 s=0.0211264      iter 8 r=0.0105751 s=0.0128797      iter 9 r=0.00652473 s=0.0081953      iter 10 r=0.00407171 s=0.00544353      iter 11 r=0.00257974 s=0.00371766      iter 12 r=0.00165766 s=0.0025963      iter 13 r=0.00107901 s=0.00184187   Finished lambda 1/1 in 0.0s   Final ADMM refit completed.   [1] "We have:"   [1] 100 1 5   [1] "--------------------------------------"   [1] "Generating data ..."   [1] "Number of non zeros is: 5"   [1] "Data generated."   [1] "--------------------------------------"      Refitting at selected lambda with ADMM logs...      Starting lambda 1/1: 0.05    lambda 1/1 = 0.05      iter 1 r=0.938376 s=0.402581      iter 2 r=0.386388 s=0.351783      iter 3 r=0.174349 s=0.213626      iter 4 r=0.0894817 s=0.118771      iter 5 r=0.0499279 s=0.0651281      iter 6 r=0.0292555 s=0.0362484      iter 7 r=0.017375 s=0.0211264      iter 8 r=0.0105751 s=0.0128797      iter 9 r=0.00652473 s=0.0081953      iter 10 r=0.00407171 s=0.00544353      iter 11 r=0.00257974 s=0.00371766      iter 12 r=0.00165766 s=0.0025963      iter 13 r=0.00107901 s=0.00184187   Finished lambda 1/1 in 0.0s   Final ADMM refit completed.   [ FAIL 1 | WARN 1 | SKIP 0 | PASS 154 ]      ══ Failed tests ════════════════════════════════════════════════════════════════   ── Error ('test-cca_group_rrr.R:76:3'): cca_group computes the same solutions across solvers ──   Error in `Rmosek::mosek(prob, opts)`: Unknown exported object to be built. Please use 'Rmosek::mosek_attachbuilder' to complete the installation of Rmosek.   Backtrace:        ▆     1. └─ccar3::cca_group_rrr(...) at test-cca_group_rrr.R:76:3     2. └─ccar3:::solve_group_rrr_cvxr(X, tilde_Y, groups, lambda, thresh_0 = thresh_0)     3. └─CVXR (local) cvxr_psolve(prob)     4. └─CVXR::solve_via_data(...)     5. ├─S7::S7_dispatch()     6. └─CVXR (local) `method(solve_via_data, CVXR::SolvingChain)`(...)     7. └─CVXR::solve_via_data(...)     8. ├─S7::S7_dispatch()     9. └─CVXR (local) `method(solve_via_data, CVXR::Mosek_Solver)`(...)    10. └─Rmosek::mosek(prob, opts)      [ FAIL 1 | WARN 1 | SKIP 0 | PASS 154 ]   Error:   ! Test failures.   Execution halted
  • checking PDF version of manual ... [2s/2s] OK
  • DONE Status: 1 ERROR
  • using check arguments '--no-clean-on-error '