CRAN Package Check Results for Maintainer ‘Julien Chiquet <julien.chiquet at inra.fr>’

Last updated on 2019-11-18 20:47:51 CET.

Package ERROR WARN NOTE OK
aricode 12
missSBM 2 2 8
PLNmodels 3 1 8
quadrupen 3 9
simone 12

Package aricode

Current CRAN status: OK: 12

Package missSBM

Current CRAN status: ERROR: 2, NOTE: 2, OK: 8

Version: 0.2.1
Check: top-level files
Result: NOTE
    ‘configure’: /bin/bash is not portable
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc

Version: 0.2.1
Check: running tests for arch ‘i386’
Result: ERROR
     Running 'testthat.R' [47s]
    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
Flavor: r-oldrel-windows-ix86+x86_64

Version: 0.2.1
Check: running tests for arch ‘x64’
Result: ERROR
     Running 'testthat.R' [54s]
    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: 0.000678
    
    
     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
     iteration #: 18
     iteration #: 19
     iteration #: 20
     iteration #: 21
    
     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
     iteration #: 18
     iteration #: 19
     iteration #: 20
     iteration #: 21
    
    
     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
Flavor: r-oldrel-windows-ix86+x86_64

Version: 0.2.1
Check: tests
Result: ERROR
     Running ‘testthat.R’ [43s/43s]
    Running the tests in ‘tests/testthat.R’ failed.
    Last 13 lines of output:
     iteration #: 21
    
    
     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
Flavor: r-oldrel-osx-x86_64

Package PLNmodels

Current CRAN status: WARN: 3, NOTE: 1, OK: 8

Version: 0.9.2
Check: installed package size
Result: NOTE
     installed size is 9.9Mb
     sub-directories of 1Mb or more:
     doc 1.6Mb
     libs 7.4Mb
Flavors: r-devel-linux-x86_64-fedora-clang, r-release-osx-x86_64, r-oldrel-osx-x86_64

Version: 0.9.2
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building ‘Import_data.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    1 samples were dropped from the abundance matrix for lack of associated covariates.
    --- finished re-building ‘Import_data.Rmd’
    
    --- re-building ‘PLN.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    corrplot 0.84 loaded
    
    Attaching package: 'dplyr'
    
    The following object is masked from 'package:gridExtra':
    
     combine
    
    The following objects are masked from 'package:stats':
    
     filter, lag
    
    The following objects are masked from 'package:base':
    
     intersect, setdiff, setequal, union
    
    Warning: Transformation introduced infinite values in continuous x-axis
    Quitting from lines 186-190 (PLN.Rmd)
    Error: processing vignette 'PLN.Rmd' failed with diagnostics:
    unused argument (options = options)
    --- failed re-building ‘PLN.Rmd’
    
    --- re-building ‘PLNLDA.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    Warning in kable_markdown(x = c("3302930", "3307296", "3348069", "3394105", :
     The table should have a header (column names)
    Warning in kable_markdown(x = c("Che", "Hyc", "Hym", "Hys", "Psy", "Aga", :
     The table should have a header (column names)
    Warning: glm.fit: algorithm did not converge
    Warning: glm.fit: fitted rates numerically 0 occurred
    --- finished re-building ‘PLNLDA.Rmd’
    
    --- re-building ‘PLNPCA.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    corrplot 0.84 loaded
    Warning in kable_markdown(x = c("Che", "Hyc", "Hym", "Hys", "Psy", "Aga", :
     The table should have a header (column names)
    Warning in kable_markdown(x = c("-1.606816", "3.835259", "7.562147", "6.244162", :
     The table should have a header (column names)
    Warning: Transformation introduced infinite values in continuous x-axis
    Warning: Removed 584 rows containing missing values (geom_point).
    --- finished re-building ‘PLNPCA.Rmd’
    
    --- re-building ‘PLNnetwork.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    Warning: Transformation introduced infinite values in continuous x-axis
    Warning: Removed 588 rows containing missing values (geom_point).
    --- finished re-building ‘PLNnetwork.Rmd’
    
    --- re-building ‘Trichoptera.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    --- finished re-building ‘Trichoptera.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘PLN.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-patched-solaris-x86

Version: 0.9.2
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
    --- re-building ‘Import_data.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    1 samples were dropped from the abundance matrix for lack of associated covariates.
    --- finished re-building ‘Import_data.Rmd’
    
    --- re-building ‘PLN.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    corrplot 0.84 loaded
    
    Attaching package: 'dplyr'
    
    The following object is masked from 'package:gridExtra':
    
     combine
    
    The following objects are masked from 'package:stats':
    
     filter, lag
    
    The following objects are masked from 'package:base':
    
     intersect, setdiff, setequal, union
    
    Warning: Transformation introduced infinite values in continuous x-axis
    Quitting from lines 186-190 (PLN.Rmd)
    Error: processing vignette 'PLN.Rmd' failed with diagnostics:
    unused argument (options = options)
    --- failed re-building ‘PLN.Rmd’
    
    --- re-building ‘PLNLDA.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    Warning in kable_markdown(x = c("1738153", "1740638", "1763806", "1789813", :
     The table should have a header (column names)
    Warning in kable_markdown(x = c("Che", "Hyc", "Hym", "Hys", "Psy", "Aga", :
     The table should have a header (column names)
    Warning: glm.fit: algorithm did not converge
    Warning: glm.fit: fitted rates numerically 0 occurred
    --- finished re-building ‘PLNLDA.Rmd’
    
    --- re-building ‘PLNPCA.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    corrplot 0.84 loaded
    Warning in kable_markdown(x = c("Che", "Hyc", "Hym", "Hys", "Psy", "Aga", :
     The table should have a header (column names)
    Warning in kable_markdown(x = c("-1.596876", "3.888390", "7.624847", "6.250576", :
     The table should have a header (column names)
    Warning: Transformation introduced infinite values in continuous x-axis
    Warning: Removed 584 rows containing missing values (geom_point).
    --- finished re-building ‘PLNPCA.Rmd’
    
    --- re-building ‘PLNnetwork.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    Warning: Transformation introduced infinite values in continuous x-axis
    Warning: Removed 589 rows containing missing values (geom_point).
    --- finished re-building ‘PLNnetwork.Rmd’
    
    --- re-building ‘Trichoptera.Rmd’ using rmarkdown
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    --- finished re-building ‘Trichoptera.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘PLN.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-release-osx-x86_64

Version: 0.9.2
Check: re-building of vignette outputs
Result: WARN
    Error in re-building vignettes:
     ...
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    1 samples were dropped from the abundance matrix for lack of associated covariates.
    Warning in engine$weave(file, quiet = quiet, encoding = enc) :
     Pandoc (>= 1.12.3) and/or pandoc-citeproc not available. Falling back to R Markdown v1.
    corrplot 0.84 loaded
    
    Attaching package: 'dplyr'
    
    The following object is masked from 'package:gridExtra':
    
     combine
    
    The following objects are masked from 'package:stats':
    
     filter, lag
    
    The following objects are masked from 'package:base':
    
     intersect, setdiff, setequal, union
    
    Warning: Transformation introduced infinite values in continuous x-axis
    Quitting from lines 186-190 (PLN.Rmd)
    Error: processing vignette 'PLN.Rmd' failed with diagnostics:
    unused argument (options = options)
    Execution halted
Flavor: r-oldrel-osx-x86_64

Package quadrupen

Current CRAN status: NOTE: 3, OK: 9

Version: 0.2-7
Check: installed package size
Result: NOTE
     installed size is 9.5Mb
     sub-directories of 1Mb or more:
     libs 9.0Mb
Flavors: r-devel-linux-x86_64-fedora-clang, r-release-osx-x86_64, r-oldrel-osx-x86_64

Package simone

Current CRAN status: OK: 12