Package: corrselect
Title: Correlation-Based and Model-Based Predictor Pruning
Version: 3.1.0
Authors@R: 
    person("Gilles", "Colling", email = "gilles.colling051@gmail.com", role = c("aut", "cre"))
Description: 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').
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.3
LinkingTo: Rcpp
Imports: Rcpp, methods, stats
Suggests: 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, svglite, data.table
VignetteBuilder: knitr
URL: https://gillescolling.com/corrselect/
BugReports: https://github.com/gcol33/corrselect/issues
Depends: R (>= 3.5)
LazyData: true
NeedsCompilation: yes
Packaged: 2026-01-08 10:56:20 UTC; Gilles Colling
Author: Gilles Colling [aut, cre]
Maintainer: Gilles Colling <gilles.colling051@gmail.com>
Repository: CRAN
Date/Publication: 2026-01-08 15:00:02 UTC
Built: R 4.4.3; aarch64-apple-darwin20; 2026-01-08 16:42:22 UTC; unix
Archs: corrselect.so.dSYM
