Running 'testthat.R' [330s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > 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 
   162.06    3.01  165.28