GAReg: Genetic Algorithms in Regression

Provides a genetic algorithm framework for regression problems requiring discrete optimization over model spaces with unknown or varying dimension, where gradient-based methods and exhaustive enumeration are impractical. Uses a compact chromosome representation for tasks including spline knot placement and best-subset variable selection, with constraint-preserving crossover and mutation, exact uniform initialization under spacing constraints, steady-state replacement, and optional island-model parallelization from Lu, Lund, and Lee (2010, <doi:10.1214/09-AOAS289>). The computation is built on the 'GA' engine of Scrucca (2017, <doi:10.32614/RJ-2017-008>) and 'changepointGA' engine from Li and Lu (2024, <doi:10.48550/arXiv.2410.15571>). In challenging high-dimensional settings, 'GAReg' enables efficient search and delivers near-optimal solutions when alternative algorithms are not well-justified.

Version:	0.1.0
Depends:	R (≥ 4.3.0)
Imports:	stats, splines, utils, methods, changepointGA, GA
Suggests:	MASS, knitr, rmarkdown
Published:	2026-02-09
DOI:	10.32614/CRAN.package.GAReg (may not be active yet)
Author:	Mo Li [aut, cre], QiQi Lu [aut], Robert Lund [aut], Xueheng Shi [aut]
Maintainer:	Mo Li <mo.li at louisiana.edu>
BugReports:	https://github.com/mli171/GAReg/issues
License:	Apache License (== 2.0)
URL:	https://github.com/mli171/GAReg
NeedsCompilation:	no
Materials:	README
CRAN checks:	GAReg results

Documentation:

Reference manual:	GAReg.html , GAReg.pdf
Vignettes:	A brief guide to GAReg (source, R code)

Downloads:

Package source:	GAReg_0.1.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): GAReg_0.1.0.tgz, r-oldrel (arm64): GAReg_0.1.0.tgz, r-release (x86_64): GAReg_0.1.0.tgz, r-oldrel (x86_64): GAReg_0.1.0.tgz

Linking:

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