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SelectBoost

2.3.0

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

3packages depend
6.6Kdownloads / year
test coverage
13/13checks pass

Overview

About
Maintained by Frederic BertrandFirst published 2019-05-276 releasesCRAN page ↗GitHub ↗

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.

Install

Health

CRAN checks
13OK
Slowest check: 3.4 min · r-oldrel-windows-x86_64
Code health
Yes
Tests · ratio 0.02
not tracked
Coverage
100%
Documentation · exports
13
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 1,160 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
99%
Return-value docs
100%
References docs
61%

Downloads

6.6K
CRAN downloads in the past year
Rank #5,807 · ~18/day · ~548/mo
Daily download trend is not available in this view yet.
22830 days
1.4K90 days
6.6K1 year
Compare downloads with other packages →
Also on169 r2u18 c2d4u

Repository

Repository
7Stars
2Forks
0Open issues
0Open PRs
5Releases
53Commits
1Contributors
selection-algorithmprecisionrecallconfidencecorrelationcorrelation-structuremodelling
53 commits · Last activity 2025-09-24

Stars over time

2022-12-01 · 72026-07-07 · 7

Repository practices

Upstream repositoryBeta

3 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/fbertran/selectboost on 2026-08-16.

Continuous integration (1)
GitHub Actions
Docs source (1)
README.Rmd
Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
15 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.5
Imports (13)
larsglmnetigraphparallelmsgpsRfastmethodsCascadegraphicsgrDevicesvarbvssplsabind
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
3direct
0indirect

Code & Tests

Datasets

People & History

People (4)
Maintainer (1)
Maintainer, Author
Authors (2)
Maintainer, Author
Contributors (2)
Contributor
Contributor
Package Timeline

6 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 2.3.0Latest
    2025-09-14 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • 2.2.2
    2022-11-30 · diff ↗
  • 2.2.1
    2022-11-29 · diff ↗
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • 2.2.0
    2021-03-20 · diff ↗
  • R
    R 4.0.0 released · 2020-04-24
  • 2.0.0
    2020-02-23 · diff ↗
  • 1.4.0
    2019-05-27
  • R
    R 3.6.0 released · 2019-04-26

Package metadata

First published
2019-05-27
Total releases
6 / 7 yrs
License
GPL-3 OSI
Minimum R
≥ 3.5
Bundled data
846 KB / 12 files
Download size
967 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SelectBoost")
Bertrand, F., Aouadi, I., Jung, N., & Maumy-Bertrand, M. (2025). SelectBoost: A General Algorithm to Enhance the Performance of Variable Selection Methods in Correlated Datasets (Version 2.3.0) [Computer software]. https://doi.org/10.32614/CRAN.package.SelectBoost

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SelectBoost version 2.3.0 [Data set]. HJJB, LLC. Data release v2026-08-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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