CatReg: Solution Paths for Linear and Logistic Regression Models with Categorical Predictors, with SCOPE Penalty

Computes solutions for linear and logistic regression models with potentially high-dimensional categorical predictors. This is done by applying a nonconvex penalty (SCOPE) and computing solutions in an efficient path-wise fashion. The scaling of the solution paths is selected automatically. Includes functionality for selecting tuning parameter lambda by k-fold cross-validation and early termination based on information criteria. Solutions are computed by cyclical block-coordinate descent, iterating an innovative dynamic programming algorithm to compute exact solutions for each block.

Version: 2.0.3
Imports: Rcpp (≥ 1.0.1), Rdpack
LinkingTo: Rcpp
Published: 2021-06-14
Author: Benjamin Stokell [aut], Daniel Grose [ctb, cre], Rajen Shah [ctb]
Maintainer: Daniel Grose <dan.grose at lancaster.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: CatReg results

Documentation:

Reference manual: CatReg.pdf

Downloads:

Package source: CatReg_2.0.3.tar.gz
Windows binaries: r-devel: CatReg_2.0.3.zip, r-devel-UCRT: CatReg_2.0.3.zip, r-release: CatReg_2.0.3.zip, r-oldrel: CatReg_2.0.3.zip
macOS binaries: r-release (arm64): CatReg_2.0.3.tgz, r-release (x86_64): CatReg_2.0.3.tgz, r-oldrel: CatReg_2.0.3.tgz
Old sources: CatReg archive

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