Package evaluation of VarianceComponentModels on Julia 1.10.9 (96dc2d8c45*) started at 2025-06-06T13:28:45.824 ################################################################################ # Set-up # Installing PkgEval dependencies (TestEnv)... Set-up completed after 5.03s ################################################################################ # Installation # Installing VarianceComponentModels... Resolving package versions... Installed Ipopt ─ v0.8.0 Updating `~/.julia/environments/v1.10/Project.toml` [813005db] + VarianceComponentModels v0.1.3 Updating `~/.julia/environments/v1.10/Manifest.toml` [6e4b80f9] + BenchmarkTools v1.6.0 [b99e7846] + BinaryProvider v0.5.10 ⌅ [523fee87] + CodecBzip2 v0.7.2 [944b1d66] + CodecZlib v0.7.8 [34da2185] + Compat v4.16.0 ⌅ [b6b21f68] + Ipopt v0.8.0 [692b3bcd] + JLLWrappers v1.7.0 [682c06a0] + JSON v0.21.4 ⌅ [b8f27783] + MathOptInterface v0.10.9 [fdba3010] + MathProgBase v0.7.8 ⌅ [d8a4904e] + MutableArithmetics v0.3.3 [bac558e1] + OrderedCollections v1.8.1 [69de0a69] + Parsers v2.8.3 ⌅ [aea7be01] + PrecompileTools v1.2.1 [21216c6a] + Preferences v1.4.3 ⌅ [3bb67fe8] + TranscodingStreams v0.9.13 [813005db] + VarianceComponentModels v0.1.3 [ae81ac8f] + ASL_jll v0.1.3+0 [6e34b625] + Bzip2_jll v1.0.9+0 ⌅ [9cc047cb] + Ipopt_jll v3.13.4+2 [d00139f3] + METIS_jll v5.1.3+0 ⌅ [d7ed1dd3] + MUMPS_seq_jll v5.2.1+4 ⌅ [656ef2d0] + OpenBLAS32_jll v0.3.24+0 [0dad84c5] + ArgTools v1.1.1 [56f22d72] + Artifacts [2a0f44e3] + Base64 [ade2ca70] + Dates [f43a241f] + Downloads v1.6.0 [7b1f6079] + FileWatching [b77e0a4c] + InteractiveUtils [b27032c2] + LibCURL v0.6.4 [76f85450] + LibGit2 [8f399da3] + Libdl [37e2e46d] + LinearAlgebra [56ddb016] + Logging [d6f4376e] + Markdown [a63ad114] + Mmap [ca575930] + NetworkOptions v1.2.0 [44cfe95a] + Pkg v1.10.0 [de0858da] + Printf [9abbd945] + Profile [3fa0cd96] + REPL [9a3f8284] + Random [ea8e919c] + SHA v0.7.0 [9e88b42a] + Serialization [6462fe0b] + Sockets [2f01184e] + SparseArrays v1.10.0 [10745b16] + Statistics v1.10.0 [fa267f1f] + TOML v1.0.3 [a4e569a6] + Tar v1.10.0 [8dfed614] + Test [cf7118a7] + UUIDs [4ec0a83e] + Unicode [e66e0078] + CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] + LibCURL_jll v8.4.0+0 [e37daf67] + LibGit2_jll v1.6.4+0 [29816b5a] + LibSSH2_jll v1.11.0+1 [c8ffd9c3] + MbedTLS_jll v2.28.2+1 [14a3606d] + MozillaCACerts_jll v2023.1.10 [4536629a] + OpenBLAS_jll v0.3.23+4 [bea87d4a] + SuiteSparse_jll v7.2.1+1 [83775a58] + Zlib_jll v1.2.13+1 [8e850b90] + libblastrampoline_jll v5.11.0+0 [8e850ede] + nghttp2_jll v1.52.0+1 [3f19e933] + p7zip_jll v17.4.0+2 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m` Building Ipopt → `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/539b23ab8fb86c6cc3e8cacaeb1f784415951be5/build.log` Installation completed after 7.99s ################################################################################ # Precompilation # Precompiling PkgEval dependencies... Precompiling package dependencies... Precompilation completed after 98.51s ################################################################################ # Testing # Testing VarianceComponentModels Status `/tmp/jl_M1Pjpp/Project.toml` ⌅ [b6b21f68] Ipopt v0.8.0 [fdba3010] MathProgBase v0.7.8 [813005db] VarianceComponentModels v0.1.3 [37e2e46d] LinearAlgebra [de0858da] Printf [9a3f8284] Random [2f01184e] SparseArrays v1.10.0 [10745b16] Statistics v1.10.0 [8dfed614] Test Status `/tmp/jl_M1Pjpp/Manifest.toml` [6e4b80f9] BenchmarkTools v1.6.0 [b99e7846] BinaryProvider v0.5.10 ⌅ [523fee87] CodecBzip2 v0.7.2 [944b1d66] CodecZlib v0.7.8 [34da2185] Compat v4.16.0 ⌅ [b6b21f68] Ipopt v0.8.0 [692b3bcd] JLLWrappers v1.7.0 [682c06a0] JSON v0.21.4 ⌅ [b8f27783] MathOptInterface v0.10.9 [fdba3010] MathProgBase v0.7.8 ⌅ [d8a4904e] MutableArithmetics v0.3.3 [bac558e1] OrderedCollections v1.8.1 [69de0a69] Parsers v2.8.3 ⌅ [aea7be01] PrecompileTools v1.2.1 [21216c6a] Preferences v1.4.3 ⌅ [3bb67fe8] TranscodingStreams v0.9.13 [813005db] VarianceComponentModels v0.1.3 [ae81ac8f] ASL_jll v0.1.3+0 [6e34b625] Bzip2_jll v1.0.9+0 ⌅ [9cc047cb] Ipopt_jll v3.13.4+2 [d00139f3] METIS_jll v5.1.3+0 ⌅ [d7ed1dd3] MUMPS_seq_jll v5.2.1+4 ⌅ [656ef2d0] OpenBLAS32_jll v0.3.24+0 [0dad84c5] ArgTools v1.1.1 [56f22d72] Artifacts [2a0f44e3] Base64 [ade2ca70] Dates [f43a241f] Downloads v1.6.0 [7b1f6079] FileWatching [b77e0a4c] InteractiveUtils [b27032c2] LibCURL v0.6.4 [76f85450] LibGit2 [8f399da3] Libdl [37e2e46d] LinearAlgebra [56ddb016] Logging [d6f4376e] Markdown [a63ad114] Mmap [ca575930] NetworkOptions v1.2.0 [44cfe95a] Pkg v1.10.0 [de0858da] Printf [9abbd945] Profile [3fa0cd96] REPL [9a3f8284] Random [ea8e919c] SHA v0.7.0 [9e88b42a] Serialization [6462fe0b] Sockets [2f01184e] SparseArrays v1.10.0 [10745b16] Statistics v1.10.0 [fa267f1f] TOML v1.0.3 [a4e569a6] Tar v1.10.0 [8dfed614] Test [cf7118a7] UUIDs [4ec0a83e] Unicode [e66e0078] CompilerSupportLibraries_jll v1.1.1+0 [deac9b47] LibCURL_jll v8.4.0+0 [e37daf67] LibGit2_jll v1.6.4+0 [29816b5a] LibSSH2_jll v1.11.0+1 [c8ffd9c3] MbedTLS_jll v2.28.2+1 [14a3606d] MozillaCACerts_jll v2023.1.10 [4536629a] OpenBLAS_jll v0.3.23+4 [bea87d4a] SuiteSparse_jll v7.2.1+1 [83775a58] Zlib_jll v1.2.13+1 [8e850b90] libblastrampoline_jll v5.11.0+0 [8e850ede] nghttp2_jll v1.52.0+1 [3f19e933] p7zip_jll v17.4.0+2 Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. Testing Running tests... Test Summary: | Pass Total Time vech | 7 7 1.5s Test Summary: | Pass Total Time trilind | 2 2 2.3s Test Summary: | Pass Total Time triuind | 14 14 0.2s Test Summary: | Pass Total Time commutation | 7 7 2.1s Test Summary: | Pass Total Time duplication | 4 4 4.5s Test Summary: | Pass Total Time chol_gradient | 1 1 9.4s Test Summary: | Pass Total Time kron_gradient | 1 1 0.0s Test Summary: | Pass Total Time kronaxpy | 1 1 0.7s Test Summary: | Pass Total Time bump_diag | 3 3 0.1s Test Summary: | Pass Total Time clamp_diag | 1 1 1.0s [ Info: VarianceComponentModel type [ Info: TwoVarCompModelRotate type [ Info: VarianceComponentVariate type [ Info: Forming VarianceComponentModel from data [ Info: Pre-compute eigen-decomposition and rotate data [ Info: Test generalized eigen-decomposition [ Info: VarianceComponentModel from TwoVarCompVariateRotate [ Info: VarianceComponentAuxData from VarianceComponentVariate [ Info: Query functions [ Info: Mean, covariance, and residual of model [ Info: Forming VarianceComponentModel from data [ Info: Pre-compute eigen-decomposition and rotate data [ Info: Evaluate log-pdf [ Info: Evaluate gradient [ Info: Evaluate Fisher information matrix of Σ [ Info: Evaluate Fisher information matrix of B [ Info: Find MLE using Fisher scoring ┌ Warning: `cholesky(A::Union{StridedMatrix, RealHermSymComplexHerm{<:Real, <:StridedMatrix}}, ::Val{true}; tol = 0.0, check::Bool = true)` is deprecated, use `cholesky(A, RowMaximum(); tol, check)` instead. │ caller = mle_fs!(vcmodel::VarianceComponentModels.VarianceComponentModel{Float64, 2, Matrix{Float64}, Matrix{Float64}}, vcdatarot::VarianceComponentModels.TwoVarCompVariateRotate{Float64, Matrix{Float64}, Matrix{Float64}}; maxiter::Int64, solver::Symbol, qpsolver::Symbol, verbose::Bool) at two_variance_component.jl:939 └ @ VarianceComponentModels ~/.julia/packages/VarianceComponentModels/F0JJD/src/two_variance_component.jl:939 ┌ Warning: `cholesky(A::Union{StridedMatrix, RealHermSymComplexHerm{<:Real, <:StridedMatrix}}, ::Val{true}; tol = 0.0, check::Bool = true)` is deprecated, use `cholesky(A, RowMaximum(); tol, check)` instead. │ caller = mle_fs!(vcmodel::VarianceComponentModels.VarianceComponentModel{Float64, 2, Matrix{Float64}, Matrix{Float64}}, vcdatarot::VarianceComponentModels.TwoVarCompVariateRotate{Float64, Matrix{Float64}, Matrix{Float64}}; maxiter::Int64, solver::Symbol, qpsolver::Symbol, verbose::Bool) at two_variance_component.jl:940 └ @ VarianceComponentModels ~/.julia/packages/VarianceComponentModels/F0JJD/src/two_variance_component.jl:940 ****************************************************************************** This program contains Ipopt, a library for large-scale nonlinear optimization. Ipopt is released as open source code under the Eclipse Public License (EPL). For more information visit https://github.com/coin-or/Ipopt ****************************************************************************** This is Ipopt version 3.13.4, running with linear solver mumps. NOTE: Other linear solvers might be more efficient (see Ipopt documentation). Number of nonzeros in equality constraint Jacobian...: 0 Number of nonzeros in inequality constraint Jacobian.: 0 Number of nonzeros in Lagrangian Hessian.............: 21 Total number of variables............................: 6 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 0 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 5.6036298e+02 0.00e+00 1.00e+02 0.0 0.00e+00 - 0.00e+00 0.00e+00 0 5 4.5966683e+02 0.00e+00 3.48e+00 -11.0 4.34e-01 - 1.00e+00 1.00e+00f 1 MaxS 10 4.5893335e+02 0.00e+00 8.65e-02 -11.0 2.27e-02 - 1.00e+00 1.00e+00f 1 MaxS 15 4.5893332e+02 0.00e+00 8.88e-04 -11.0 2.00e-05 - 1.00e+00 1.00e+00f 1 MaxS 20 4.5893332e+02 0.00e+00 1.08e-05 -11.0 2.43e-07 - 1.00e+00 1.00e+00f 1 MaxS 25 4.5893332e+02 0.00e+00 1.30e-07 -11.0 2.94e-09 - 1.00e+00 1.00e+00f 1 MaxSA Number of Iterations....: 28 (scaled) (unscaled) Objective...............: 4.1079451465233359e+02 4.5893332475611919e+02 Dual infeasibility......: 9.1993423186458290e-09 1.0277363998978641e-08 Constraint violation....: 0.0000000000000000e+00 0.0000000000000000e+00 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 9.1993423186458290e-09 1.0277363998978641e-08 Number of objective function evaluations = 29 Number of objective gradient evaluations = 29 Number of equality constraint evaluations = 0 Number of inequality constraint evaluations = 0 Number of equality constraint Jacobian evaluations = 0 Number of inequality constraint Jacobian evaluations = 0 Number of Lagrangian Hessian evaluations = 28 Total CPU secs in IPOPT (w/o function evaluations) = 5.617 Total CPU secs in NLP function evaluations = 0.189 EXIT: Optimal Solution Found. ┌ Warning: `cholesky(A::Union{StridedMatrix, RealHermSymComplexHerm{<:Real, <:StridedMatrix}}, ::Val{true}; tol = 0.0, check::Bool = true)` is deprecated, use `cholesky(A, RowMaximum(); tol, check)` instead. │ caller = mle_fs!(vcmodel::VarianceComponentModels.VarianceComponentModel{Float64, 2, Matrix{Float64}, Matrix{Float64}}, vcdatarot::Matrix{VarianceComponentModels.TwoVarCompVariateRotate{Float64, Matrix{Float64}, Matrix{Float64}}}; maxiter::Int64, solver::Symbol, qpsolver::Symbol, verbose::Bool) at two_variance_component.jl:939 └ @ VarianceComponentModels ~/.julia/packages/VarianceComponentModels/F0JJD/src/two_variance_component.jl:939 ┌ Warning: `cholesky(A::Union{StridedMatrix, RealHermSymComplexHerm{<:Real, <:StridedMatrix}}, ::Val{true}; tol = 0.0, check::Bool = true)` is deprecated, use `cholesky(A, RowMaximum(); tol, check)` instead. │ caller = mle_fs!(vcmodel::VarianceComponentModels.VarianceComponentModel{Float64, 2, Matrix{Float64}, Matrix{Float64}}, vcdatarot::Matrix{VarianceComponentModels.TwoVarCompVariateRotate{Float64, Matrix{Float64}, Matrix{Float64}}}; maxiter::Int64, solver::Symbol, qpsolver::Symbol, verbose::Bool) at two_variance_component.jl:940 └ @ VarianceComponentModels ~/.julia/packages/VarianceComponentModels/F0JJD/src/two_variance_component.jl:940 This is Ipopt version 3.13.4, running with linear solver mumps. NOTE: Other linear solvers might be more efficient (see Ipopt documentation). Number of nonzeros in equality constraint Jacobian...: 0 Number of nonzeros in inequality constraint Jacobian.: 0 Number of nonzeros in Lagrangian Hessian.............: 21 Total number of variables............................: 6 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 0 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 1.1143831e+03 0.00e+00 1.34e+02 0.0 0.00e+00 - 0.00e+00 0.00e+00 0 5 9.1899214e+02 0.00e+00 2.60e+00 -11.0 3.35e-01 - 1.00e+00 1.00e+00f 1 MaxS 10 9.1786666e+02 0.00e+00 3.22e-02 -11.0 8.72e-03 - 1.00e+00 1.00e+00f 1 MaxS 15 9.1786665e+02 0.00e+00 3.72e-04 -11.0 1.53e-05 - 1.00e+00 1.00e+00f 1 MaxS 20 9.1786665e+02 0.00e+00 1.03e-05 -11.0 4.22e-07 - 1.00e+00 1.00e+00f 1 MaxS 25 9.1786665e+02 0.00e+00 2.83e-07 -11.0 1.16e-08 - 1.00e+00 1.00e+00f 1 MaxSA 30 9.1786665e+02 0.00e+00 7.78e-09 -11.0 3.20e-10 - 1.00e+00 1.00e+00f 1 MaxS Number of Iterations....: 30 (scaled) (unscaled) Objective...............: 2.7309429398060712e+02 9.1786664951223804e+02 Dual infeasibility......: 7.7829900853063435e-09 2.6158536411216232e-08 Constraint violation....: 0.0000000000000000e+00 0.0000000000000000e+00 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 7.7829900853063435e-09 2.6158536411216232e-08 Number of objective function evaluations = 31 Number of objective gradient evaluations = 31 Number of equality constraint evaluations = 0 Number of inequality constraint evaluations = 0 Number of equality constraint Jacobian evaluations = 0 Number of inequality constraint Jacobian evaluations = 0 Number of Lagrangian Hessian evaluations = 30 Total CPU secs in IPOPT (w/o function evaluations) = 0.708 Total CPU secs in NLP function evaluations = 0.181 EXIT: Optimal Solution Found. vcmfs.B = [1.1294040061633739 0.9701981564504818; 1.4801376153533605 0.9433189982076383] Bse_fs = [0.26323584934522076 0.14991701511274821; 0.21978022838470848 0.14168965681345225] B = [1.0 1.0; 1.0 1.0] [ Info: Find MLE using MM algorithm MM Algorithm Iter Objective -------- ------------- 0 -7e+02 1 -5e+02 2 -5e+02 3 -5e+02 4 -5e+02 5 -5e+02 6 -5e+02 7 -5e+02 8 -5e+02 9 -5e+02 10 -5e+02 20 -5e+02 30 -5e+02 40 -5e+02 50 -5e+02 60 -5e+02 70 -5e+02 80 -5e+02 90 -5e+02 100 -5e+02 110 -5e+02 120 -5e+02 130 -5e+02 140 -5e+02 vcmmm.B = [1.1294243113053708 0.9701757915893713; 1.4799950069464538 0.9435085544636724] Bse_mm = [0.26349094680134105 0.14981992713753522; 0.21999844341176394 0.14159213144717417] B = [1.0 1.0; 1.0 1.0] MM Algorithm Iter Objective -------- ------------- 0 -1e+03 1 -1e+03 2 -1e+03 3 -9e+02 4 -9e+02 5 -9e+02 6 -9e+02 7 -9e+02 8 -9e+02 9 -9e+02 10 -9e+02 20 -9e+02 30 -9e+02 40 -9e+02 50 -9e+02 60 -9e+02 70 -9e+02 80 -9e+02 90 -9e+02 100 -9e+02 110 -9e+02 120 -9e+02 130 -9e+02 140 -9e+02 [ Info: Find MLE using Fisher scoring (linear equality + box constraints) This is Ipopt version 3.13.4, running with linear solver mumps. NOTE: Other linear solvers might be more efficient (see Ipopt documentation). Number of nonzeros in equality constraint Jacobian...: 0 Number of nonzeros in inequality constraint Jacobian.: 0 Number of nonzeros in Lagrangian Hessian.............: 21 Total number of variables............................: 6 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 0 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 5.6539866e+02 0.00e+00 1.00e+02 0.0 0.00e+00 - 0.00e+00 0.00e+00 0 5 4.6171514e+02 0.00e+00 3.17e+00 -11.0 4.30e-01 - 1.00e+00 1.00e+00f 1 MaxS 10 4.6103905e+02 0.00e+00 4.79e-02 -11.0 8.82e-03 - 1.00e+00 1.00e+00f 1 MaxS 15 4.6103904e+02 0.00e+00 5.58e-04 -11.0 1.34e-05 - 1.00e+00 1.00e+00f 1 MaxS 20 4.6103904e+02 0.00e+00 8.39e-06 -11.0 2.01e-07 - 1.00e+00 1.00e+00f 1 MaxSA 25 4.6103904e+02 0.00e+00 1.26e-07 -11.0 3.02e-09 - 1.00e+00 1.00e+00f 1 MaxSA Number of Iterations....: 29 (scaled) (unscaled) Objective...............: 3.7976962155150704e+02 4.6103903880560023e+02 Dual infeasibility......: 4.3883729188571478e-09 5.3274699123242628e-09 Constraint violation....: 0.0000000000000000e+00 0.0000000000000000e+00 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 4.3883729188571478e-09 5.3274699123242628e-09 Number of objective function evaluations = 30 Number of objective gradient evaluations = 30 Number of equality constraint evaluations = 0 Number of inequality constraint evaluations = 0 Number of equality constraint Jacobian evaluations = 0 Number of inequality constraint Jacobian evaluations = 0 Number of Lagrangian Hessian evaluations = 29 Total CPU secs in IPOPT (w/o function evaluations) = 0.333 Total CPU secs in NLP function evaluations = 0.738 EXIT: Optimal Solution Found. vcmfs.B = [1.0 0.9920007674082094; 1.0 0.9989069653547288] [ Info: Find MLE using MM algorithm (linear equality + box constraints) MM Algorithm Iter Objective -------- ------------- 0 -7e+02 1 -5e+02 2 -5e+02 3 -5e+02 4 -5e+02 5 -5e+02 6 -5e+02 7 -5e+02 8 -5e+02 9 -5e+02 10 -5e+02 20 -5e+02 30 -5e+02 40 -5e+02 50 -5e+02 60 -5e+02 70 -5e+02 80 -5e+02 90 -5e+02 100 -5e+02 110 -5e+02 120 -5e+02 vcmm.B = [1.0 0.9919830326455855; 1.0 0.9990692151968458] [ Info: Heritability estimation (h, h_se) = ([0.24682039805979908, 0.016994867527299645], [0.11948190741443744, 0.17221061024286052]) [ Info: test fit_mle (FS) This is Ipopt version 3.13.4, running with linear solver mumps. NOTE: Other linear solvers might be more efficient (see Ipopt documentation). Number of nonzeros in equality constraint Jacobian...: 0 Number of nonzeros in inequality constraint Jacobian.: 0 Number of nonzeros in Lagrangian Hessian.............: 21 Total number of variables............................: 6 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 0 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 5.6036298e+02 0.00e+00 1.00e+02 0.0 0.00e+00 - 0.00e+00 0.00e+00 0 5 4.5966683e+02 0.00e+00 3.48e+00 -11.0 4.34e-01 - 1.00e+00 1.00e+00f 1 MaxS 10 4.5893335e+02 0.00e+00 8.65e-02 -11.0 2.27e-02 - 1.00e+00 1.00e+00f 1 MaxS 15 4.5893332e+02 0.00e+00 8.88e-04 -11.0 2.00e-05 - 1.00e+00 1.00e+00f 1 MaxS 20 4.5893332e+02 0.00e+00 1.08e-05 -11.0 2.43e-07 - 1.00e+00 1.00e+00f 1 MaxS 25 4.5893332e+02 0.00e+00 1.30e-07 -11.0 2.94e-09 - 1.00e+00 1.00e+00f 1 MaxSA Number of Iterations....: 28 (scaled) (unscaled) Objective...............: 4.1079451465233359e+02 4.5893332475611919e+02 Dual infeasibility......: 9.1993423186458290e-09 1.0277363998978641e-08 Constraint violation....: 0.0000000000000000e+00 0.0000000000000000e+00 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 9.1993423186458290e-09 1.0277363998978641e-08 Number of objective function evaluations = 29 Number of objective gradient evaluations = 29 Number of equality constraint evaluations = 0 Number of inequality constraint evaluations = 0 Number of equality constraint Jacobian evaluations = 0 Number of inequality constraint Jacobian evaluations = 0 Number of Lagrangian Hessian evaluations = 28 Total CPU secs in IPOPT (w/o function evaluations) = 0.019 Total CPU secs in NLP function evaluations = 0.146 EXIT: Optimal Solution Found. (vcmmle.B, Bse_mle, B) = ([1.1294040061721913 0.9701981564519464; 1.4801376153548786 0.9433189982078287], [0.26323584934522076 0.14991701511274821; 0.21978022838470848 0.14168965681345225], [1.0 1.0; 1.0 1.0]) This is Ipopt version 3.13.4, running with linear solver mumps. NOTE: Other linear solvers might be more efficient (see Ipopt documentation). Number of nonzeros in equality constraint Jacobian...: 0 Number of nonzeros in inequality constraint Jacobian.: 0 Number of nonzeros in Lagrangian Hessian.............: 21 Total number of variables............................: 6 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 0 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 1.1143831e+03 0.00e+00 1.34e+02 0.0 0.00e+00 - 0.00e+00 0.00e+00 0 5 9.1899214e+02 0.00e+00 2.60e+00 -11.0 3.35e-01 - 1.00e+00 1.00e+00f 1 MaxS 10 9.1786666e+02 0.00e+00 3.22e-02 -11.0 8.72e-03 - 1.00e+00 1.00e+00f 1 MaxS 15 9.1786665e+02 0.00e+00 3.72e-04 -11.0 1.53e-05 - 1.00e+00 1.00e+00f 1 MaxS 20 9.1786665e+02 0.00e+00 1.03e-05 -11.0 4.22e-07 - 1.00e+00 1.00e+00f 1 MaxS 25 9.1786665e+02 0.00e+00 2.83e-07 -11.0 1.16e-08 - 1.00e+00 1.00e+00f 1 MaxSA 30 9.1786665e+02 0.00e+00 7.78e-09 -11.0 3.20e-10 - 1.00e+00 1.00e+00f 1 MaxS Number of Iterations....: 30 (scaled) (unscaled) Objective...............: 2.7309429398060712e+02 9.1786664951223804e+02 Dual infeasibility......: 7.7829900853063435e-09 2.6158536411216232e-08 Constraint violation....: 0.0000000000000000e+00 0.0000000000000000e+00 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 7.7829900853063435e-09 2.6158536411216232e-08 Number of objective function evaluations = 31 Number of objective gradient evaluations = 31 Number of equality constraint evaluations = 0 Number of inequality constraint evaluations = 0 Number of equality constraint Jacobian evaluations = 0 Number of inequality constraint Jacobian evaluations = 0 Number of Lagrangian Hessian evaluations = 30 Total CPU secs in IPOPT (w/o function evaluations) = 0.023 Total CPU secs in NLP function evaluations = 0.157 EXIT: Optimal Solution Found. [ Info: test fit_mle (MM) MM Algorithm Iter Objective -------- ------------- 0 -7e+02 1 -5e+02 2 -5e+02 3 -5e+02 4 -5e+02 5 -5e+02 6 -5e+02 7 -5e+02 8 -5e+02 9 -5e+02 10 -5e+02 20 -5e+02 30 -5e+02 40 -5e+02 50 -5e+02 60 -5e+02 70 -5e+02 80 -5e+02 90 -5e+02 100 -5e+02 110 -5e+02 120 -5e+02 130 -5e+02 140 -5e+02 (vcmmle.B, Bse_mle, B) = ([1.1294243113053708 0.9701757915893713; 1.4799950069464538 0.9435085544636724], [0.26349094680134105 0.14981992713753522; 0.21999844341176394 0.14159213144717417], [1.0 1.0; 1.0 1.0]) [ Info: test fit_reml (FS) This is Ipopt version 3.13.4, running with linear solver mumps. NOTE: Other linear solvers might be more efficient (see Ipopt documentation). Number of nonzeros in equality constraint Jacobian...: 0 Number of nonzeros in inequality constraint Jacobian.: 0 Number of nonzeros in Lagrangian Hessian.............: 21 Total number of variables............................: 6 variables with only lower bounds: 0 variables with lower and upper bounds: 0 variables with only upper bounds: 0 Total number of equality constraints.................: 0 Total number of inequality constraints...............: 0 inequality constraints with only lower bounds: 0 inequality constraints with lower and upper bounds: 0 inequality constraints with only upper bounds: 0 iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls 0 5.6657288e+02 0.00e+00 1.00e+02 0.0 0.00e+00 - 0.00e+00 0.00e+00 0 5 4.6218671e+02 0.00e+00 3.25e+00 -11.0 4.35e-01 - 1.00e+00 1.00e+00f 1 MaxS 10 4.6145290e+02 0.00e+00 7.42e-02 -11.0 2.23e-02 - 1.00e+00 1.00e+00f 1 MaxS 15 4.6145288e+02 0.00e+00 6.46e-04 -11.0 1.76e-05 - 1.00e+00 1.00e+00f 1 MaxS 20 4.6145288e+02 0.00e+00 7.36e-06 -11.0 2.01e-07 - 1.00e+00 1.00e+00f 1 MaxSA 25 4.6145288e+02 0.00e+00 8.35e-08 -11.0 2.28e-09 - 1.00e+00 1.00e+00f 1 MaxSA Number of Iterations....: 28 (scaled) (unscaled) Objective...............: 3.7129035848599005e+02 4.6145288025515595e+02 Dual infeasibility......: 5.6784909110612326e-09 7.0574307318319563e-09 Constraint violation....: 0.0000000000000000e+00 0.0000000000000000e+00 Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+00 Overall NLP error.......: 5.6784909110612326e-09 7.0574307318319563e-09 Number of objective function evaluations = 29 Number of objective gradient evaluations = 29 Number of equality constraint evaluations = 0 Number of inequality constraint evaluations = 0 Number of equality constraint Jacobian evaluations = 0 Number of inequality constraint Jacobian evaluations = 0 Number of Lagrangian Hessian evaluations = 28 Total CPU secs in IPOPT (w/o function evaluations) = 0.017 Total CPU secs in NLP function evaluations = 0.003 EXIT: Optimal Solution Found. (vcmreml.B, Bse_reml, B) = ([1.1343181538815563 0.9709855572756602; 1.4791688013223476 0.9431576203900794], [0.27523715686214706 0.15049369982118188; 0.22940713434712473 0.14208494286763393], [1.0 1.0; 1.0 1.0]) [ Info: test fit_reml (MM) MM Algorithm Iter Objective -------- ------------- 0 -6e+02 1 -5e+02 2 -5e+02 3 -5e+02 4 -5e+02 5 -5e+02 6 -5e+02 7 -5e+02 8 -5e+02 9 -5e+02 10 -5e+02 20 -5e+02 30 -5e+02 40 -5e+02 50 -5e+02 60 -5e+02 70 -5e+02 80 -5e+02 90 -5e+02 100 -5e+02 110 -5e+02 120 -5e+02 130 -5e+02 140 -5e+02 (vcmreml.B, Bse_reml, B) = ([1.1343391285637392 0.970963001153965; 1.4790264213034676 0.9433466923298472], [0.27550946456123876 0.15039917917019172; 0.22964270865571204 0.14198946323480538], [1.0 1.0; 1.0 1.0]) Testing VarianceComponentModels tests passed Testing completed after 88.89s PkgEval succeeded after 203.58s