Package: randomGLM 1.10-1

randomGLM: Random General Linear Model Prediction

A bagging predictor based on generalized linear models (GLMs) is implemented. The method is published in Song, Langfelder and Horvath (2013) <doi:10.1186/1471-2105-14-5>.

Authors:Lin Song, Peter Langfelder

randomGLM_1.10-1.tar.gz
randomGLM_1.10-1.zip(r-4.5)randomGLM_1.10-1.zip(r-4.4)randomGLM_1.10-1.zip(r-4.3)
randomGLM_1.10-1.tgz(r-4.4-any)randomGLM_1.10-1.tgz(r-4.3-any)
randomGLM_1.10-1.tar.gz(r-4.5-noble)randomGLM_1.10-1.tar.gz(r-4.4-noble)
randomGLM_1.10-1.tgz(r-4.4-emscripten)randomGLM_1.10-1.tgz(r-4.3-emscripten)
randomGLM.pdf |randomGLM.html✨
randomGLM/json (API)

# Install 'randomGLM' in R:
install.packages('randomGLM', repos = c('https://plangfelder.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • brainCancer - The brain cancer data set
  • mini - An example data set derived from the brain cancer data set

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.45 score 1 stars 28 scripts 215 downloads 4 exports 78 dependencies

Last updated 3 years agofrom:c7538391e3. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 27 2024
R-4.5-winOKOct 27 2024
R-4.5-linuxOKOct 27 2024
R-4.4-winOKOct 27 2024
R-4.4-macOKOct 27 2024
R-4.3-winOKOct 27 2024
R-4.3-macOKOct 27 2024

Exports:accuracyMeasurespredict.randomGLMrandomGLMthinRandomGLM

Dependencies:abindbackportsbase64encbslibcachemcheckmatecliclustercodetoolscolorspacedata.tabledigestdoParallelevaluatefansifarverfastmapfontawesomeforeachforeignFormulafsgeometryggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobanditeratorsjquerylibjsonliteknitrlabelinglatticelifecyclelinproglpSolvemagicmagrittrMASSMatrixmatrixStatsmemoisemgcvmimemunsellnlmennetpillarpkgconfigR6rappdirsRColorBrewerRcppRcppProgressrlangrmarkdownrpartrstudioapisassscalesstringistringrsurvivaltibbletinytexutf8vctrsviridisviridisLitewithrxfunyaml