SelectBoost: A General Algorithm to Enhance the Performance of Variable Selection Methods in Correlated Datasets

An implementation of the selectboost algorithm (Bertrand et al. 2020, 'Bioinformatics', <doi:10.1093/bioinformatics/btaa855>), which is a general algorithm that improves the precision of any existing variable selection method. This algorithm is based on highly intensive simulations and takes into account the correlation structure of the data. It can either produce a confidence index for variable selection or it can be used in an experimental design planning perspective.

Version:	2.3.0
Depends:	R (≥ 3.5)
Imports:	lars, glmnet, igraph, parallel, msgps, Rfast, methods, Cascade, graphics, grDevices, varbvs, spls, abind
Suggests:	knitr, markdown, rmarkdown, mixOmics, CascadeData, testthat (≥ 3.0.0)
Published:	2025-09-14
DOI:	10.32614/CRAN.package.SelectBoost
Author:	Frederic Bertrand [cre, aut], Myriam Maumy-Bertrand [aut], Ismail Aouadi [ctb], Nicolas Jung [ctb]
Maintainer:	Frederic Bertrand <frederic.bertrand at lecnam.net>
BugReports:	https://github.com/fbertran/SelectBoost/issues/
License:	GPL-3
URL:	https://fbertran.github.io/SelectBoost/, https://github.com/fbertran/SelectBoost/
NeedsCompilation:	no
Classification/MSC:	62H11, 62J12, 62J99
Citation:	SelectBoost citation info
Materials:	README, NEWS
CRAN checks:	SelectBoost results

Documentation:

Reference manual:	SelectBoost.html , SelectBoost.pdf
Vignettes:	Benchmarking the SelectBoost Package for Network Reverse Engineering (source, R code) Towards Confidence Estimates in Cascade Networks using the SelectBoost Package (source, R code) Simulation Tools Provided With the Selectboost Package (source, R code)

Downloads:

Package source:	SelectBoost_2.3.0.tar.gz
Windows binaries:	r-devel: SelectBoost_2.3.0.zip, r-release: SelectBoost_2.3.0.zip, r-oldrel: SelectBoost_2.3.0.zip
macOS binaries:	r-release (arm64): SelectBoost_2.3.0.tgz, r-oldrel (arm64): SelectBoost_2.3.0.tgz, r-release (x86_64): SelectBoost_2.3.0.tgz, r-oldrel (x86_64): SelectBoost_2.3.0.tgz
Old sources:	SelectBoost archive

Reverse dependencies:

Reverse imports:

Patterns, SelectBoost.gamlss

Linking:

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