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SelectBoost

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

v2.3.0 · Sep 13, 2025 · GPL-3

Description

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.

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CRAN Check Status

14 OK
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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Reverse Dependencies (2)

Dependency Network

Dependencies Reverse dependencies lars glmnet igraph msgps Rfast Cascade varbvs spls abind Patterns SelectBoost.gamlss SelectBoost

Version History

new 2.3.0 Mar 10, 2026
updated 2.3.0 ← 2.2.2 diff Sep 13, 2025
updated 2.2.2 ← 2.2.1 diff Nov 29, 2022
updated 2.2.1 ← 2.2.0 diff Nov 28, 2022
updated 2.2.0 ← 2.0.0 diff Mar 19, 2021
updated 2.0.0 ← 1.4.0 diff Feb 22, 2020
new 1.4.0 May 26, 2019