R Under development (unstable) (2024-03-03 r86036 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > library(testthat) > library(PLNmodels) This is packages 'PLNmodels' version 1.2.0 Use future::plan(multicore/multisession) to speed up PLNPCA/PLNmixture/stability_selection. > > test_check("PLNmodels") Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a spherical covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a diagonal covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a fixed covariance PLN model with nlopt optimizer Post-treatments... DONE! Performing discriminant Analysis... DONE! Performing discriminant Analysis... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a diagonal covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a spherical covariance PLN model with nlopt optimizer Post-treatments... DONE! Performing discriminant Analysis... DONE! Performing discriminant Analysis... DONE! Performing discriminant Analysis... DONE! Performing discriminant Analysis... DONE! Performing discriminant Analysis... DONE! Performing discriminant Analysis... DONE! Performing discriminant Analysis... DONE! Initialization... Adjusting 3 PLN mixture models. number of cluster = 1 number of cluster = 2 number of cluster = 3 Post-treatments DONE! Initialization... Adjusting 3 PLN mixture models. number of cluster = 1 number of cluster = 2 number of cluster = 3 Post-treatments DONE! Initialization... Adjusting 3 PLN mixture models. number of cluster = 1 number of cluster = 2 number of cluster = 3 Post-treatments DONE! Initialization... Adjusting 3 PLN mixture models. number of cluster = 1 number of cluster = 2 number of cluster = 3 Post-treatments DONE! Initialization... Adjusting 3 PLN mixture models. number of cluster = 1 number of cluster = 2 number of cluster = 3 Post-treatments DONE! Initialization... Adjusting 2 PLN mixture models. number of cluster = 2 number of cluster = 4 Smoothing PLN mixture models. Going backward + Going forward + Post-treatments DONE! Initialization... Adjusting 1 PLN mixture models. Initialization... Adjusting 3 PLN mixture models. number of cluster = 1 number of cluster = 2 number of cluster = 3 Post-treatments DONE! Initialization... Adjusting 3 PLN mixture models. number of cluster = 1 number of cluster = 2 number of cluster = 3 Post-treatments DONE! Initialization... Adjusting 3 PLN mixture models. number of cluster = 1 number of cluster = 2 number of cluster = 3 Post-treatments DONE! Initialization... Adjusting 30 PLN with sparse inverse covariance estimation Joint optimization alternating gradient descent and graphical-lasso sparsifying penalty = 1.931881 sparsifying penalty = 1.784422 sparsifying penalty = 1.648219 sparsifying penalty = 1.522412 sparsifying penalty = 1.406207 sparsifying penalty = 1.298873 sparsifying penalty = 1.199731 sparsifying penalty = 1.108157 sparsifying penalty = 1.023572 sparsifying penalty = 0.9454436 sparsifying penalty = 0.8732787 sparsifying penalty = 0.8066221 sparsifying penalty = 0.7450533 sparsifying penalty = 0.688184 sparsifying penalty = 0.6356555 sparsifying penalty = 0.5871365 sparsifying penalty = 0.5423209 sparsifying penalty = 0.500926 sparsifying penalty = 0.4626907 sparsifying penalty = 0.4273739 sparsifying penalty = 0.3947528 sparsifying penalty = 0.3646217 sparsifying penalty = 0.3367904 sparsifying penalty = 0.3110835 sparsifying penalty = 0.2873388 sparsifying penalty = 0.2654065 sparsifying penalty = 0.2451482 sparsifying penalty = 0.2264363 sparsifying penalty = 0.2091526 sparsifying penalty = 0.1931881 Post-treatments DONE! Stability Selection for PLNnetwork: subsampling: ++ Stability Selection for PLNnetwork: subsampling: ++ Initialization... Adjusting 30 PLN with sparse inverse covariance estimation Joint optimization alternating gradient descent and graphical-lasso sparsifying penalty = 1.931881 sparsifying penalty = 1.784422 sparsifying penalty = 1.648219 sparsifying penalty = 1.522412 sparsifying penalty = 1.406207 sparsifying penalty = 1.298873 sparsifying penalty = 1.199731 sparsifying penalty = 1.108157 sparsifying penalty = 1.023572 sparsifying penalty = 0.9454436 sparsifying penalty = 0.8732787 sparsifying penalty = 0.8066221 sparsifying penalty = 0.7450533 sparsifying penalty = 0.688184 sparsifying penalty = 0.6356555 sparsifying penalty = 0.5871365 sparsifying penalty = 0.5423209 sparsifying penalty = 0.500926 sparsifying penalty = 0.4626907 sparsifying penalty = 0.4273739 sparsifying penalty = 0.3947528 sparsifying penalty = 0.3646217 sparsifying penalty = 0.3367904 sparsifying penalty = 0.3110835 sparsifying penalty = 0.2873388 sparsifying penalty = 0.2654065 sparsifying penalty = 0.2451482 sparsifying penalty = 0.2264363 sparsifying penalty = 0.2091526 sparsifying penalty = 0.1931881 Post-treatments DONE! Stability Selection for PLNnetwork: subsampling: ++ Initialization... Initialization... Initialization... Initialization... Adjusting 30 PLN with sparse inverse covariance estimation Joint optimization alternating gradient descent and graphical-lasso sparsifying penalty = 193.1881 sparsifying penalty = 178.4422 sparsifying penalty = 164.8219 sparsifying penalty = 152.2412 sparsifying penalty = 140.6207 sparsifying penalty = 129.8873 sparsifying penalty = 119.9731 sparsifying penalty = 110.8157 sparsifying penalty = 102.3572 sparsifying penalty = 94.54436 sparsifying penalty = 87.32787 sparsifying penalty = 80.66221 sparsifying penalty = 74.50533 sparsifying penalty = 68.8184 sparsifying penalty = 63.56555 sparsifying penalty = 58.71365 sparsifying penalty = 54.23209 sparsifying penalty = 50.0926 sparsifying penalty = 46.26907 sparsifying penalty = 42.73739 sparsifying penalty = 39.47528 sparsifying penalty = 36.46217 sparsifying penalty = 33.67904 sparsifying penalty = 31.10835 sparsifying penalty = 28.73388 sparsifying penalty = 26.54065 sparsifying penalty = 24.51482 sparsifying penalty = 22.64363 sparsifying penalty = 20.91526 sparsifying penalty = 19.31881 Post-treatments DONE! Stability Selection for PLNnetwork: subsampling: ++ Initialization... Adjusting 30 PLN with sparse inverse covariance estimation Joint optimization alternating gradient descent and graphical-lasso sparsifying penalty = 7.40614 sparsifying penalty = 6.840836 sparsifying penalty = 6.318681 sparsifying penalty = 5.836381 sparsifying penalty = 5.390895 sparsifying penalty = 4.979413 sparsifying penalty = 4.599339 sparsifying penalty = 4.248275 sparsifying penalty = 3.924008 sparsifying penalty = 3.624492 sparsifying penalty = 3.347837 sparsifying penalty = 3.0923 sparsifying penalty = 2.856267 sparsifying penalty = 2.638251 sparsifying penalty = 2.436875 sparsifying penalty = 2.250871 sparsifying penalty = 2.079064 sparsifying penalty = 1.920371 sparsifying penalty = 1.77379 sparsifying penalty = 1.638398 sparsifying penalty = 1.513341 sparsifying penalty = 1.397829 sparsifying penalty = 1.291134 sparsifying penalty = 1.192583 sparsifying penalty = 1.101554 sparsifying penalty = 1.017473 sparsifying penalty = 0.9398103 sparsifying penalty = 0.8680754 sparsifying penalty = 0.8018159 sparsifying penalty = 0.740614 Post-treatments DONE! Rank approximation = 3 Rank approximation = 1 Rank approximation = 2 Rank approximation = 5 Rank approximation = 4 Initialization... Adjusting 5 PLN models for PCA analysis. Rank approximation = 5 Rank approximation = 1 Rank approximation = 2 Rank approximation = 3 Rank approximation = 4 Post-treatments DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Computing variational estimator of the variance... Computing jackknife estimator of the variance... Computing bootstrap estimator of the variance... Initialization... Adjusting a full covariance PLN model with nlopt optimizer Post-treatments... DONE! Initialization... Adjusting 3 PLN models for PCA analysis. Rank approximation = 3 Rank approximation = 2 Rank approximation = 1 Post-treatments DONE! Initialization... Adjusting 30 PLN with sparse inverse covariance estimation Joint optimization alternating gradient descent and graphical-lasso sparsifying penalty = 1.296303 sparsifying penalty = 1.197357 sparsifying penalty = 1.105964 sparsifying penalty = 1.021546 sparsifying penalty = 0.9435727 sparsifying penalty = 0.8715506 sparsifying penalty = 0.8050259 sparsifying penalty = 0.743579 sparsifying penalty = 0.6868222 sparsifying penalty = 0.6343977 sparsifying penalty = 0.5859746 sparsifying penalty = 0.5412477 sparsifying penalty = 0.4999347 sparsifying penalty = 0.4617751 sparsifying penalty = 0.4265282 sparsifying penalty = 0.3939717 sparsifying penalty = 0.3639002 sparsifying penalty = 0.336124 sparsifying penalty = 0.3104679 sparsifying penalty = 0.2867702 sparsifying penalty = 0.2648813 sparsifying penalty = 0.2446631 sparsifying penalty = 0.2259882 sparsifying penalty = 0.2087387 sparsifying penalty = 0.1928058 sparsifying penalty = 0.1780891 sparsifying penalty = 0.1644957 sparsifying penalty = 0.1519399 sparsifying penalty = 0.1403425 sparsifying penalty = 0.1296303 Post-treatments DONE! Initialization... Adjusting 3 PLN mixture models. number of cluster = 1 number of cluster = 2 number of cluster = 3 Post-treatments DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and row specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and col specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and covar specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and covar specific parameter(s) in Zero inflation component. DONE! Initialization... Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and covar specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with full covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with spherical covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with diagonal covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with fixed covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting a ZI-PLN model with sparse covariance model and single specific parameter(s) in Zero inflation component. DONE! Initialization... Adjusting 30 ZI-PLN with sparse inverse covariance estimation and single specific parameter(s) in Zero inflation component. sparsifying penalty = 1.934579 sparsifying penalty = 1.786915 sparsifying penalty = 1.650521 sparsifying penalty = 1.524538 sparsifying penalty = 1.408171 sparsifying penalty = 1.300687 sparsifying penalty = 1.201407 sparsifying penalty = 1.109704 sparsifying penalty = 1.025001 sparsifying penalty = 0.946764 sparsifying penalty = 0.8744983 sparsifying penalty = 0.8077486 sparsifying penalty = 0.7460939 sparsifying penalty = 0.6891452 sparsifying penalty = 0.6365433 sparsifying penalty = 0.5879565 sparsifying penalty = 0.5430783 sparsifying penalty = 0.5016256 sparsifying penalty = 0.4633369 sparsifying penalty = 0.4279708 sparsifying penalty = 0.3953042 sparsifying penalty = 0.3651309 sparsifying penalty = 0.3372608 sparsifying penalty = 0.311518 sparsifying penalty = 0.2877401 sparsifying penalty = 0.2657771 sparsifying penalty = 0.2454906 sparsifying penalty = 0.2267525 sparsifying penalty = 0.2094447 sparsifying penalty = 0.1934579 DONE! Stability Selection for ZIPLNnetwork: subsampling: ++ Stability Selection for ZIPLNnetwork: subsampling: ++ Stability Selection for ZIPLNnetwork: subsampling: ++ Initialization... Adjusting 30 ZI-PLN with sparse inverse covariance estimation and single specific parameter(s) in Zero inflation component. sparsifying penalty = 1.934579 sparsifying penalty = 1.786915 sparsifying penalty = 1.650521 sparsifying penalty = 1.524538 sparsifying penalty = 1.408171 sparsifying penalty = 1.300687 sparsifying penalty = 1.201407 sparsifying penalty = 1.109704 sparsifying penalty = 1.025001 sparsifying penalty = 0.946764 sparsifying penalty = 0.8744983 sparsifying penalty = 0.8077486 sparsifying penalty = 0.7460939 sparsifying penalty = 0.6891452 sparsifying penalty = 0.6365433 sparsifying penalty = 0.5879565 sparsifying penalty = 0.5430783 sparsifying penalty = 0.5016256 sparsifying penalty = 0.4633369 sparsifying penalty = 0.4279708 sparsifying penalty = 0.3953042 sparsifying penalty = 0.3651309 sparsifying penalty = 0.3372608 sparsifying penalty = 0.311518 sparsifying penalty = 0.2877401 sparsifying penalty = 0.2657771 sparsifying penalty = 0.2454906 sparsifying penalty = 0.2267525 sparsifying penalty = 0.2094447 sparsifying penalty = 0.1934579 DONE! Stability Selection for ZIPLNnetwork: subsampling: ++ Initialization... Initialization... Initialization... Initialization... Adjusting 30 ZI-PLN with sparse inverse covariance estimation and single specific parameter(s) in Zero inflation component. sparsifying penalty = 193.4579 sparsifying penalty = 178.6915 sparsifying penalty = 165.0521 sparsifying penalty = 152.4538 sparsifying penalty = 140.8171 sparsifying penalty = 130.0687 sparsifying penalty = 120.1407 sparsifying penalty = 110.9704 sparsifying penalty = 102.5001 sparsifying penalty = 94.6764 sparsifying penalty = 87.44983 sparsifying penalty = 80.77486 sparsifying penalty = 74.60939 sparsifying penalty = 68.91452 sparsifying penalty = 63.65433 sparsifying penalty = 58.79565 sparsifying penalty = 54.30783 sparsifying penalty = 50.16256 sparsifying penalty = 46.33369 sparsifying penalty = 42.79708 sparsifying penalty = 39.53042 sparsifying penalty = 36.51309 sparsifying penalty = 33.72608 sparsifying penalty = 31.1518 sparsifying penalty = 28.77401 sparsifying penalty = 26.57771 sparsifying penalty = 24.54906 sparsifying penalty = 22.67525 sparsifying penalty = 20.94447 sparsifying penalty = 19.34579 DONE! Stability Selection for ZIPLNnetwork: subsampling: ++[ FAIL 0 | WARN 1 | SKIP 0 | PASS 866 ] [ FAIL 0 | WARN 1 | SKIP 0 | PASS 866 ] > > proc.time() user system elapsed 126.59 2.03 128.62