ProxReg: Linear Models for Prediction and Classification using Proximal Operators

Implements optimization techniques for Lasso regression, R.Tibshirani(1996)<doi:10.1111/j.2517-6161.1996.tb02080.x> using Fast Iterative Shrinkage-Thresholding Algorithm (FISTA) and Iterative Shrinkage-Thresholding Algorithm (ISTA) based on proximal operators, A.Beck(2009)<doi:10.1137/080716542>. The package is useful for high-dimensional regression problems and includes cross-validation procedures to select optimal penalty parameters.

Version:	1.1.1
Imports:	dplyr, EBImage, glmnet
Suggests:	knitr, rmarkdown
Published:	2025-06-13
Author:	YingHong Chen [aut, cre], Ferran Reverter Comes [aut], Esteban Vegas Lozano [aut]
Maintainer:	YingHong Chen <yinghongchen1402 at gmail.com>
License:	MIT + file LICENSE
NeedsCompilation:	no
Language:	en-US
CRAN checks:	ProxReg results

Documentation:

Reference manual:	ProxReg.pdf
Vignettes:	Manual for the package: linearreg (source, R code)

Downloads:

Package source:	ProxReg_1.1.1.tar.gz
Windows binaries:	r-devel: ProxReg_0.1.1.zip, r-release: ProxReg_0.1.1.zip, r-oldrel: ProxReg_0.1.1.zip
macOS binaries:	r-release (arm64): ProxReg_1.1.1.tgz, r-oldrel (arm64): ProxReg_1.1.1.tgz, r-release (x86_64): ProxReg_0.1.1.tgz, r-oldrel (x86_64): ProxReg_0.1.1.tgz
Old sources:	ProxReg archive

Linking:

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