CRAN Package Check Results for Package DevTreatRules

Last updated on 2019-11-25 05:47:12 CET.

Check Details

Version: 1.0.0
Check: R code for possible problems
Result: NOTE
    DoPrediction: no visible global function definition for
     'predict.cv.glmnet'
    PredictRule: no visible global function definition for
     'predict.cv.glmnet'
    Undefined global functions or variables:
     predict.cv.glmnet
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-devel-windows-ix86+x86_64-gcc8, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-windows-ix86+x86_64

Version: 1.0.0
Check: examples
Result: ERROR
    Running examples in 'DevTreatRules-Ex.R' failed
    The error most likely occurred in:
    
    > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
    > ### Name: CompareRulesOnValidation
    > ### Title: Build treatment rules on a development dataset and evaluate
    > ### performance on an independent validation dataset
    > ### Aliases: CompareRulesOnValidation
    >
    > ### ** Examples
    >
    > set.seed(123)
    > example.split <- SplitData(data=obsStudyGeneExpressions,
    + n.sets=3, split.proportions=c(0.5, 0.25, 0.25))
    > development.data <- example.split[example.split$partition == "development", ]
    > validation.data <- example.split[example.split$partition == "validation", ]
    > model.selection <- CompareRulesOnValidation(development.data=development.data,
    + validation.data=validation.data,
    + study.design.development="observational",
    + vec.approaches=c("split.regression", "OWL.framework", "direct.interactions"),
    + vec.rule.methods=c("glm.regression", "lasso"),
    + vec.propensity.methods="logistic.regression",
    + name.outcome.development="no_relapse",
    + type.outcome.development="binary",
    + name.treatment.development="intervention",
    + names.influencing.treatment.development=c("prognosis", "clinic", "age"),
    + names.influencing.rule.development=c("age", paste0("gene_", 1:10)),
    + desirable.outcome.development=TRUE)
    Error in predict.cv.glmnet(one.cv.glmnet, newx = features, s = optimal.lambda, :
     could not find function "predict.cv.glmnet"
    Calls: CompareRulesOnValidation -> BuildRule -> DoPrediction
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 1.0.0
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building 'my-vignette.Rmd' using rmarkdown
    
    Attaching package: 'dplyr'
    
    The following objects are masked from 'package:stats':
    
     filter, lag
    
    The following objects are masked from 'package:base':
    
     intersect, setdiff, setequal, union
    
    Quitting from lines 84-97 (my-vignette.Rmd)
    Error: processing vignette 'my-vignette.Rmd' failed with diagnostics:
    could not find function "predict.cv.glmnet"
    --- failed re-building 'my-vignette.Rmd'
    
    SUMMARY: processing the following file failed:
     'my-vignette.Rmd'
    
    Error: Vignette re-building failed.
    Execution halted
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-patched-linux-x86_64, r-release-linux-x86_64

Version: 1.0.0
Check: examples
Result: ERROR
    Running examples in ‘DevTreatRules-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: CompareRulesOnValidation
    > ### Title: Build treatment rules on a development dataset and evaluate
    > ### performance on an independent validation dataset
    > ### Aliases: CompareRulesOnValidation
    >
    > ### ** Examples
    >
    > set.seed(123)
    > example.split <- SplitData(data=obsStudyGeneExpressions,
    + n.sets=3, split.proportions=c(0.5, 0.25, 0.25))
    > development.data <- example.split[example.split$partition == "development", ]
    > validation.data <- example.split[example.split$partition == "validation", ]
    > model.selection <- CompareRulesOnValidation(development.data=development.data,
    + validation.data=validation.data,
    + study.design.development="observational",
    + vec.approaches=c("split.regression", "OWL.framework", "direct.interactions"),
    + vec.rule.methods=c("glm.regression", "lasso"),
    + vec.propensity.methods="logistic.regression",
    + name.outcome.development="no_relapse",
    + type.outcome.development="binary",
    + name.treatment.development="intervention",
    + names.influencing.treatment.development=c("prognosis", "clinic", "age"),
    + names.influencing.rule.development=c("age", paste0("gene_", 1:10)),
    + desirable.outcome.development=TRUE)
    Error in predict.cv.glmnet(one.cv.glmnet, newx = features, s = optimal.lambda, :
     could not find function "predict.cv.glmnet"
    Calls: CompareRulesOnValidation -> BuildRule -> DoPrediction
    Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-devel-windows-ix86+x86_64-gcc8, r-patched-solaris-x86, r-release-windows-ix86+x86_64

Version: 1.0.0
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
    --- re-building ‘my-vignette.Rmd’ using rmarkdown
    
    Attaching package: 'dplyr'
    
    The following objects are masked from 'package:stats':
    
     filter, lag
    
    The following objects are masked from 'package:base':
    
     intersect, setdiff, setequal, union
    
    Quitting from lines 84-97 (my-vignette.Rmd)
    Error: processing vignette 'my-vignette.Rmd' failed with diagnostics:
    could not find function "predict.cv.glmnet"
    --- failed re-building ‘my-vignette.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘my-vignette.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-devel-windows-ix86+x86_64-gcc8, r-release-windows-ix86+x86_64

Version: 1.0.0
Check: re-building of vignette outputs
Result: WARN
    Error(s) in re-building vignettes:
     ...
    --- re-building ‘my-vignette.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.
    
    Attaching package: 'dplyr'
    
    The following objects are masked from 'package:stats':
    
     filter, lag
    
    The following objects are masked from 'package:base':
    
     intersect, setdiff, setequal, union
    
    Quitting from lines 84-97 (my-vignette.Rmd)
    Error: processing vignette 'my-vignette.Rmd' failed with diagnostics:
    could not find function "predict.cv.glmnet"
    --- failed re-building ‘my-vignette.Rmd’
    
    SUMMARY: processing the following file failed:
     ‘my-vignette.Rmd’
    
    Error: Vignette re-building failed.
    Execution halted
Flavor: r-patched-solaris-x86