collinear: Seamless Multicollinearity Management

System for seamless management of multicollinearity in data frames with numeric and/or categorical variables for statistical analysis and machine learning modeling. The package combines bivariate correlation (Pearson, Spearman, and Cramer's V) with variance inflation factor analysis, target encoding to transform categorical variables into numeric (Micci-Barreca, D. 2001 <doi:10.1145/507533.507538>), and a flexible feature prioritization method, to deliver a comprehensive multicollinearity management tool covering a wide range of use cases.

Version: 1.1.1
Depends: R (≥ 4.0)
Imports: dplyr
Suggests: ranger, mgcv, future, future.apply, testthat (≥ 3.0.0), spelling
Published: 2023-12-08
DOI: NA
Author: Blas M. Benito ORCID iD [aut, cre, cph]
Maintainer: Blas M. Benito <blasbenito at gmail.com>
License: MIT + file LICENSE
URL: https://blasbenito.github.io/collinear/
NeedsCompilation: no
Language: en-US
Citation: collinear citation info
Materials: README NEWS
CRAN checks: collinear results

Documentation:

Reference manual: collinear.pdf

Downloads:

Package source: collinear_1.1.1.tar.gz
Windows binaries: r-devel: collinear_1.1.1.zip, r-release: collinear_1.1.1.zip, r-oldrel: collinear_1.1.1.zip
macOS binaries: r-release (arm64): collinear_1.1.1.tgz, r-oldrel (arm64): collinear_1.1.1.tgz, r-release (x86_64): collinear_1.1.1.tgz, r-oldrel (x86_64): collinear_1.1.1.tgz
Old sources: collinear archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=collinear to link to this page.