CRAN Package Check Results for Package glmnet

Last updated on 2020-08-12 03:48:42 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 4.0-2 25.02 164.93 189.95 OK
r-devel-linux-x86_64-debian-gcc 4.0-2 26.44 121.60 148.04 OK
r-devel-linux-x86_64-fedora-clang 4.0-2 243.30 OK
r-devel-linux-x86_64-fedora-gcc 4.0-2 268.37 OK
r-devel-windows-ix86+x86_64 4.0-2 69.00 284.00 353.00 OK
r-patched-linux-x86_64 4.0-2 29.09 160.76 189.85 OK
r-patched-solaris-x86 4.0-2 264.70 ERROR
r-release-linux-x86_64 4.0-2 27.05 160.84 187.89 OK
r-release-macos-x86_64 4.0-2 OK
r-release-windows-ix86+x86_64 4.0-2 71.00 290.00 361.00 OK
r-oldrel-macos-x86_64 4.0-2 OK
r-oldrel-windows-ix86+x86_64 4.0-2 50.00 201.00 251.00 OK

Check Details

Version: 4.0-2
Check: examples
Result: ERROR
    Running examples in ‘glmnet-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: glmnet
    > ### Title: fit a GLM with lasso or elasticnet regularization
    > ### Aliases: glmnet relax.glmnet
    > ### Keywords: models regression
    >
    > ### ** Examples
    >
    >
    > # Gaussian
    > x = matrix(rnorm(100 * 20), 100, 20)
    > y = rnorm(100)
    > fit1 = glmnet(x, y)
    > print(fit1)
    
    Call: glmnet(x = x, y = y)
    
     Df %Dev Lambda
    1 0 0.00 0.197600
    2 1 0.60 0.180000
    3 1 1.10 0.164000
    4 2 1.54 0.149500
    5 4 2.79 0.136200
    6 4 4.06 0.124100
    7 4 5.11 0.113100
    8 4 5.98 0.103000
    9 5 6.78 0.093870
    10 5 7.52 0.085530
    11 6 8.20 0.077940
    12 6 8.91 0.071010
    13 6 9.49 0.064700
    14 8 10.07 0.058960
    15 9 10.60 0.053720
    16 10 11.12 0.048950
    17 12 11.57 0.044600
    18 12 11.97 0.040640
    19 12 12.31 0.037030
    20 13 12.59 0.033740
    21 13 12.88 0.030740
    22 14 13.13 0.028010
    23 14 13.35 0.025520
    24 14 13.54 0.023250
    25 14 13.69 0.021190
    26 14 13.82 0.019310
    27 14 13.93 0.017590
    28 14 14.02 0.016030
    29 14 14.09 0.014600
    30 14 14.15 0.013310
    31 15 14.20 0.012120
    32 17 14.25 0.011050
    33 17 14.28 0.010070
    34 17 14.32 0.009172
    35 18 14.34 0.008357
    36 19 14.36 0.007614
    37 19 14.39 0.006938
    38 19 14.40 0.006322
    39 19 14.42 0.005760
    40 20 14.43 0.005248
    41 20 14.44 0.004782
    42 20 14.45 0.004357
    43 20 14.46 0.003970
    44 20 14.47 0.003617
    45 20 14.48 0.003296
    46 20 14.48 0.003003
    47 20 14.49 0.002736
    48 20 14.49 0.002493
    49 20 14.49 0.002272
    50 20 14.50 0.002070
    51 20 14.50 0.001886
    52 20 14.50 0.001719
    53 20 14.50 0.001566
    54 20 14.50 0.001427
    55 20 14.50 0.001300
    56 20 14.50 0.001185
    57 20 14.50 0.001079
    58 20 14.51 0.000983
    59 20 14.51 0.000896
    60 20 14.51 0.000816
    61 20 14.51 0.000744
    62 20 14.51 0.000678
    63 20 14.51 0.000618
    64 20 14.51 0.000563
    65 20 14.51 0.000513
    66 20 14.51 0.000467
    > coef(fit1, s = 0.01) # extract coefficients at a single value of lambda
    21 x 1 sparse Matrix of class "dgCMatrix"
     1
    (Intercept) -0.1154251627
    V1 0.1003781671
    V2 0.2123146104
    V3 0.1478378877
    V4 0.0071738140
    V5 0.0017068814
    V6 .
    V7 -0.0009736938
    V8 -0.1988997621
    V9 .
    V10 0.1071297719
    V11 0.0563547748
    V12 0.0392889072
    V13 -0.1673111781
    V14 -0.0331802879
    V15 0.0322438934
    V16 0.0368881782
    V17 .
    V18 0.0013228366
    V19 0.0613253373
    V20 0.0388175403
    > predict(fit1, newx = x[1:10, ], s = c(0.01, 0.005)) # make predictions
     1 2
     [1,] 0.1623437 0.1923152
     [2,] -0.5447409 -0.5540136
     [3,] 0.3089815 0.3238559
     [4,] 0.3441108 0.3593363
     [5,] -0.4261315 -0.4431612
     [6,] 0.4629769 0.4778225
     [7,] 0.5536940 0.5777430
     [8,] 0.3760726 0.3938430
     [9,] -0.5032892 -0.5408060
    [10,] -0.3201688 -0.3367624
    >
    > # Relaxed
    > fit1r = glmnet(x, y, relax = TRUE) # can be used with any model
    >
    > # multivariate gaussian
    > y = matrix(rnorm(100 * 3), 100, 3)
    > fit1m = glmnet(x, y, family = "mgaussian")
    > plot(fit1m, type.coef = "2norm")
    >
    > # binomial
    > g2 = sample(c(0,1), 100, replace = TRUE)
    > fit2 = glmnet(x, g2, family = "binomial")
    > fit2n = glmnet(x, g2, family = binomial(link=cloglog))
    Error in elnet.fit(x, z, w, lambda, alpha, intercept, thresh = thresh, :
     NA/NaN/Inf in foreign function call (arg 25)
    Calls: glmnet -> glmnet.path -> glmnet.fit -> elnet.fit
    Execution halted
Flavor: r-patched-solaris-x86

Version: 4.0-2
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building ‘Coxnet.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     The vignette engine knitr::rmarkdown is not available, because the rmarkdown package is not installed. Please install it.
    
    (process:16066): Pango-WARNING **: failed to create cairo scaled font, expect ugly output. the offending font is 'Helvetica Medium 9'
    
    (process:16066): Pango-WARNING **: font_face status is: <unknown error status>
    
    (process:16066): Pango-WARNING **: scaled_font status is: invalid matrix (not invertible)
    
    (process:16066): Pango-WARNING **: shaping failure, expect ugly output. shape-engine='BasicEngineFc', font='Helvetica Medium 9', text='m'
    --- finished re-building ‘Coxnet.Rmd’
    
    --- re-building ‘glmnet.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     The vignette engine knitr::rmarkdown is not available, because the rmarkdown package is not installed. Please install it.
    Loading required package: lars
    Loaded lars 1.2
    
    --- finished re-building ‘glmnet.Rmd’
    
    --- re-building ‘glmnetFamily.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     The vignette engine knitr::rmarkdown is not available, because the rmarkdown package is not installed. Please install it.
    Loading required package: Matrix
    Loaded glmnet 4.0-2
    Quitting from lines 121-124 (glmnetFamily.Rmd)
    Error: processing vignette 'glmnetFamily.Rmd' failed with diagnostics:
    NA/NaN/Inf in foreign function call (arg 25)
    --- failed re-building ‘glmnetFamily.Rmd’
    
    --- re-building ‘relax.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     The vignette engine knitr::rmarkdown is not available, because the rmarkdown package is not installed. Please install it.
    --- finished re-building ‘relax.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘glmnetFamily.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-patched-solaris-x86