Package: GAReg Type: Package Title: Genetic Algorithms in Regression Version: 0.1.2 Authors@R: c( person( given = "Mo", family = "Li", role = c("aut", "cre"), email = "mo.li@louisiana.edu"), person( given = "QiQi", family = "Lu", role = "aut", email = "qlu2@vcu.edu"), person( given = "Robert", family = "Lund", role = "aut", email = "rolund@ucsc.edu"), person( given = "Xueheng", family = "Shi", role = "aut", email = "shixueheng@gmail.com") ) Description: 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, ). The computation is built on the 'GA' engine of Scrucca (2017, ) and 'changepointGA' engine from Li and Lu (2024, ). In challenging high-dimensional settings, 'GAReg' enables efficient search and delivers near-optimal solutions when alternative algorithms are not well-justified. License: Apache License (== 2.0) RoxygenNote: 7.3.3 Depends: R (>= 4.3.0) Imports: stats, splines, utils, methods, changepointGA, GA URL: https://github.com/mli171/GAReg BugReports: https://github.com/mli171/GAReg/issues Suggests: MASS, knitr, rmarkdown Encoding: UTF-8 VignetteBuilder: knitr LazyData: true Repository: https://mli171.r-universe.dev Date/Publication: 2026-04-27 04:49:13 UTC RemoteUrl: https://github.com/mli171/gareg RemoteRef: HEAD RemoteSha: 4c91d47b78ed3b660581652d6e8203039d897101 NeedsCompilation: no Packaged: 2026-06-17 10:28:29 UTC; root Author: Mo Li [aut, cre], QiQi Lu [aut], Robert Lund [aut], Xueheng Shi [aut] Maintainer: Mo Li