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
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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
randomGLM/json (API)

# Install 'randomGLM' in R:
install.packages('randomGLM', repos = c('https://plangfelder.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • brainCancer - The brain cancer data set
  • mini - An example data set derived from the brain cancer data set

On CRAN:

Conda:

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

1.57 score 1 stars 37 scripts 351 downloads 4 exports 71 dependencies

Last updated from:c7538391e3. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK170
source / vignettesOK196
linux-release-x86_64OK171
macos-release-arm64OK124
macos-oldrel-arm64OK84
windows-develOK114
windows-releaseOK104
windows-oldrelOK109
wasm-releaseOK152

Exports:accuracyMeasurespredict.randomGLMrandomGLMthinRandomGLM

Dependencies:abindbackportsbase64encbslibcachemcheckmatecliclustercodetoolscolorspacecpp11data.tabledigestdoParallelevaluatefarverfastmapfontawesomeforeachforeignFormulafsgeometryggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobanditeratorsjquerylibjsonliteknitrlabelinglatticelifecyclelinproglpSolvemagicmagrittrMASSMatrixmatrixStatsmemoisemimennetR6rappdirsRColorBrewerRcppRcppProgressrlangrmarkdownrpartrstudioapiS7sassscalesstringistringrsurvivaltinytexvctrsviridisLitewithrxfunyaml