Running 'testthat.R' [45s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library(testthat)
  > library(missSBM)
  
  Attaching package: 'missSBM'
  
  The following objects are masked from 'package:stats':
  
      simulate, smooth
  
  The following object is masked from 'package:base':
  
      sample
  
  > 
  > test_check("missSBM")
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Dyads are distributed according to a 'undirected' SBM.
  
  	Imputation assumes a 'covar-dyad' network-sampling process
   iteration #: 1 
   iteration #: 2 
   iteration #: 3 
   iteration #: 4 
   iteration #: 5 
   iteration #: 6 
   iteration #: 7 
   iteration #: 8 
   iteration #: 9 
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Dyads are distributed according to a 'undirected' SBM.
  
  	Imputation assumes a 'dyad' network-sampling process
   iteration #: 1 
   iteration #: 2 
   iteration #: 3 
   iteration #: 4 
   iteration #: 5 
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Dyads are distributed according to a 'undirected' SBM.
  
  	Imputation assumes a 'covar-node' network-sampling process
   iteration #: 1 
   iteration #: 2 
   iteration #: 3 
   iteration #: 4 
   iteration #: 5 
   iteration #: 6 
   iteration #: 7 
   iteration #: 8 
  -- 1. Failure: miss SBM with covariates and node sampling works (@test-MISSSBM-f
  error(missSBM$fittedSBM$covarParam, sbm$covarParam) is not strictly less than `tol_truth`. Difference: 0.000677
  
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Dyads are distributed according to a 'undirected' SBM.
  
  	Imputation assumes a 'node' network-sampling process
   iteration #: 1 
   iteration #: 2 
   iteration #: 3 
   iteration #: 4 
   iteration #: 5 
  
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'dyad' network-sampling process
  
   Initialization of model with 1 blocks. 
   Initialization of model with 2 blocks. 
   Initialization of model with 3 blocks. 
   Initialization of model with 4 blocks. 
   Smoothing ICL
     Going forward +++
                                                                                                      
   Smoothing ICL
     Going backward +++
                                                                                                      
   Smoothing ICL
     Going forward +++
                                                                                                      
     Going backward +++
                                                                                                      
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'dyad' network-sampling process
  
   Initialization of model with 1 blocks. 
   Initialization of model with 2 blocks. 
   Initialization of model with 3 blocks. 
   Initialization of model with 4 blocks. 
   Smoothing ICL
     Going forward +++
                                                                                                      
     Going forward +++
                                                                                                      
   Smoothing ICL
     Going backward +++
                                                                                                      
     Going backward +++
                                                                                                      
   Smoothing ICL
     Going forward +++
                                                                                                      
     Going backward +++
                                                                                                      
     Going forward +++
                                                                                                      
     Going backward +++
                                                                                                      
  Tested sampling:
   - dyad
   - node
   - double-standard
   - block-node
   - degree
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  sampling: dyad
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'dyad' network-sampling process
  
   Initialization of model with 3 blocks. 
   Performing VEM inference for model with 3 blocks.
   new better on mixture
  node
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'node' network-sampling process
  
   Initialization of model with 3 blocks. 
   Performing VEM inference for model with 3 blocks.
  double-standard
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'double-standard' network-sampling process
  
   Initialization of model with 3 blocks. 
   Performing VEM inference for model with 3 blocks.
   new better on connectivity new better on sampling parameters
  block-node
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'block-node' network-sampling process
  
   Initialization of model with 3 blocks. 
   Performing VEM inference for model with 3 blocks.
   new better on mixture new better on connectivity new better on sampling parameters
  
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'covar-dyad' network-sampling process
  
   Initialization of model with 2 blocks. 
   Performing VEM inference for model with 2 blocks.
   new better on mixture new better on connectivity
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'covar-node' network-sampling process
  
   Initialization of model with 2 blocks. 
   Performing VEM inference for model with 2 blocks.
   new better on mixture new better on connectivity
  Sampling: dyad
  Sampling: node
  Sampling: double-standard
  Sampling: block-node
  Sampling: block-dyad
   Adjusting Variational EM for Stochastic Block Model
   iteration #: 1 
   iteration #: 2 
   iteration #: 3 
   iteration #: 4 
   iteration #: 5 
   iteration #: 6 
   iteration #: 7 
   iteration #: 8 
   iteration #: 9 
   iteration #: 10 
   iteration #: 11 
   iteration #: 12 
   iteration #: 13 
   iteration #: 14 
   iteration #: 15 
   iteration #: 16 
   iteration #: 17 
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Dyads are distributed according to a 'undirected' SBM.
  
  	Imputation assumes a 'node' network-sampling process
   iteration #: 1 
   iteration #: 2 
   iteration #: 3 
   iteration #: 4 
   iteration #: 5 
   iteration #: 6 
   iteration #: 7 
   iteration #: 8 
   iteration #: 9 
   iteration #: 10 
   iteration #: 11 
   iteration #: 12 
   iteration #: 13 
   iteration #: 14 
   iteration #: 15 
   iteration #: 16 
   iteration #: 17 
  
  
   Adjusting Variational EM for Stochastic Block Model
  
  	Imputation assumes a 'node' network-sampling process
  
   Initialization of model with 3 blocks. 
   Performing VEM inference for model with 3 blocks.
  == testthat results  ===========================================================
  [ OK: 458 | SKIPPED: 0 | WARNINGS: 0 | FAILED: 1 ]
  1. Failure: miss SBM with covariates and node sampling works (@test-MISSSBM-fit-with-covariates.R#124) 
  
  Error: testthat unit tests failed
  Execution halted