Running 'testthat.R' [231s]
Running the tests in 'tests/testthat.R' failed.
Complete output:
  > library(testthat)
  > library(clustMixType)
  > 
  > test_check("clustMixType")
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  Estimated lambda: 6.768405 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  Estimated lambda: 6.768405 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  Estimated lambda: 6.768405 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  Estimated lambda: 6.768405 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  Estimated lambda: 6.768405 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  Estimated lambda: 6.768405 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  Estimated lambda: 6.768405 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  Estimated lambda: 6.768405 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  0 observation(s) with NAs.
  
  Numeric variances:
        x3       x4 
  3.256170 3.511135 
  Average numeric variance: 3.383652 
  
  Heuristic for categorical variables: (method = 1) 
         x1        x2 
  0.4998875 0.4999500 
  Average categorical variation: 0.4999188 
  
  Estimated lambda: 6.768405 
  
  Numeric variances:
        x3       x4 
  3.256170 3.511135 
  Average numeric variance: 3.383652 
  
  Heuristic for categorical variables: (method = 1) 
         x1        x2 
  0.4998875 0.4999500 
  Average categorical variation: 0.4999188 
  
  Numeric variances:
        x3       x4 
  3.256170 3.511135 
  Average numeric variance: 3.383652 
  
  Heuristic for categorical variables: (method = 1) 
         x1        x2 
  0.4998875 0.4999500 
  Average categorical variation: 0.4999188 
  
  Numeric variances:
        x3       x4 
  3.256170 3.511135 
  Average numeric variance: 3.383652 
  
  Heuristic for categorical variables: (method = 1) 
         x1        x2 
  0.4998875 0.4999500 
  Average categorical variation: 0.4999188 
  
  Numeric variances:
        x3       x4 
  3.256170 3.511135 
  Average numeric variance: 3.383652 
  
  Heuristic for categorical variables: (method = 1) 
         x1        x2 
  0.4998875 0.4999500 
  Average categorical variation: 0.4999188 
  
  Numeric variances:
        x3       x4 
  3.256170 3.511135 
  Average numeric variance: 3.383652 
  
  Heuristic for categorical variables: (method = 1) 
         x1        x2 
  0.4998875 0.4999500 
  Average categorical variation: 0.4999188 
  
  Numeric variances:
        x3       x4 
  3.256170 3.511135 
  Average numeric variance: 3.383652 
  
  Heuristic for categorical variables: (method = 1) 
         x1        x2 
  0.4998875 0.4999500 
  Average categorical variation: 0.4999188 
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  Numeric variances:
        x3       x4 
  3.256170 3.511135 
  Average numeric variance: 3.383652 
  
  Heuristic for categorical variables: (method = 1) 
         x1        x2 
  0.4998875 0.4999500 
  Average categorical variation: 0.4999188 
  
  Estimated lambda: 6.768405 
  
  0 observation(s) with NAs.
  
  Numeric variances:
        x3       x4 
  3.256170 3.511135 
  Average numeric variance: 3.383652 
  
  Heuristic for categorical variables: (method = 1) 
         x1        x2 
  0.4998875 0.4999500 
  Average categorical variation: 0.4999188 
  
  Estimated lambda: 6.768405 
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  Numeric variances:
        x3       x4 
  3.256170 3.511135 
  Average numeric variance: 3.383652 
  
  Heuristic for categorical variables: (method = 1) 
         x1        x2 
  0.4998875 0.4999500 
  Average categorical variation: 0.4999188 
  
  0 observation(s) with NAs.
  
  Numeric variances:
        x3       x4 
  3.256170 3.511135 
  Average numeric variance: 3.383652 
  
  Heuristic for categorical variables: (method = 1) 
         x1        x2 
  0.4998875 0.4999500 
  Average categorical variation: 0.4999188 
  
  # NAs in variables:
  x1 x3 
   0  0 
  0 observation(s) with NAs.
  
  Estimated lambda: 6.513805 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 
   0  0 
  0 observation(s) with NAs.
  
  # NAs in variables:
  x3 x4 
   0  0 
  0 observation(s) with NAs.
  
  # NAs in variables:
  V1 V2 
   0  0 
  0 observation(s) with NAs.
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   1  0  0  0 
  1 observation(s) with NAs.
  
  Estimated lambda: 6.783304 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   1  1  1  1 
  1 observation(s) where all variables NA.
  
  Estimated lambda: 6.783304 
  
  # NAs in variables:
  x1 x2 x3 x4 
   1  0  0  0 
  # NAs in variables:
  x1 x2 x3 x4 
   1  0  0  0 
  1 observation(s) with NAs.
  
  Estimated lambda: 6.783304 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 x3 x4 
   1  0  0  0 
  # NAs in variables:
  V1 V2 
   0 10 
  Estimated lambda: 2.222222 
  
  # NAs in variables:
  V1 V2 
   0  5 
  Estimated lambda: 40 
  
  # NAs in variables:
  V1 V2 
   0  5 
  Estimated lambda: 40 
  
  # NAs in variables:
  x1 x2 x3 x4 
   0  0  0  0 
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 
   0  0 
  0 observation(s) with NAs.
  
  Estimated lambda: 5.502435 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 
   0  0 
  0 observation(s) with NAs.
  
  Estimated lambda: 5.502435 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 
   0  0 
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 V3 
   0  0  0 
  0 observation(s) with NAs.
  
  # NAs in variables:
  Sepal.Length  Sepal.Width Petal.Length  Petal.Width      Species 
             0            0            0            0            0 
  0 observation(s) with NAs.
  
  Estimated lambda: 1.714859 
  
  0 observation(s) with NAs.
  
  # NAs in variables:
  Sepal.Length  Sepal.Width Petal.Length  Petal.Width      Species 
             0            0            0            0            0 
  0 observation(s) with NAs.
  
  # NAs in variables:
  x1 x2 
   0  0 
  0 observation(s) with NAs.
  
  Estimated lambda: 5.502435 
  
  0 observation(s) with NAs.
  
  1  cluster with only one observation
  1  cluster with only one observation
  1  cluster with only one observation
  [ FAIL 0 | WARN 34 | SKIP 0 | PASS 205 ]
  
  [ FAIL 0 | WARN 34 | SKIP 0 | PASS 205 ]
  > 
  > proc.time()
     user  system elapsed 
    69.14    3.04   72.20