corrselect: Correlation-Based and Model-Based Predictor Pruning

Provides functions for predictor pruning using association-based and model-based approaches. Includes corrPrune() for fast correlation-based pruning, modelPrune() for VIF-based regression pruning, and exact graph-theoretic algorithms (Eppstein–Löffler–Strash, Bron–Kerbosch) for exhaustive subset enumeration. Supports linear models, GLMs, and mixed models ('lme4', 'glmmTMB').

Version:	3.0.2
Depends:	R (≥ 3.5)
Imports:	Rcpp, methods, stats
LinkingTo:	Rcpp
Suggests:	svglite, GO.db, WGCNA, preprocessCore, impute, energy, minerva, lme4, glmmTMB, MASS, caret, car, carData, microbenchmark, igraph, Boruta, glmnet, corrplot, knitr, rmarkdown, testthat (≥ 3.0.0), tibble
Published:	2025-11-29
DOI:	10.32614/CRAN.package.corrselect
Author:	Gilles Colling [aut, cre]
Maintainer:	Gilles Colling <gilles.colling051 at gmail.com>
BugReports:	https://github.com/gcol33/corrselect/issues
License:	MIT + file LICENSE
URL:	https://gillescolling.com/corrselect/
NeedsCompilation:	yes
Citation:	corrselect citation info
Materials:	README, NEWS
CRAN checks:	corrselect results

Documentation:

Reference manual:	corrselect.html , corrselect.pdf
Vignettes:	Advanced Topics (source, R code) Comparison with Alternatives (source, R code) Quick Start (source, R code) Theory and Formulation (source, R code) Complete Workflows: Real-World Examples (source, R code)

Downloads:

Package source:	corrselect_3.0.2.tar.gz
Windows binaries:	r-devel: corrselect_3.0.2.zip, r-release: corrselect_3.0.2.zip, r-oldrel: corrselect_3.0.2.zip
macOS binaries:	r-release (arm64): corrselect_3.0.2.tgz, r-oldrel (arm64): corrselect_3.0.2.tgz, r-release (x86_64): corrselect_3.0.2.tgz, r-oldrel (x86_64): corrselect_3.0.2.tgz
Old sources:	corrselect archive

Linking:

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