Robust Methods for High-Dimensional Data [R package robustHD version 0.8.2]

Andreas Alfons

robustHD: Robust Methods for High-Dimensional Data

Robust methods for high-dimensional data, in particular linear model selection techniques based on least angle regression and sparse regression. Specifically, the package implements robust least angle regression (Khan, Van Aelst & Zamar, 2007; <doi:10.1198/016214507000000950>), (robust) groupwise least angle regression (Alfons, Croux & Gelper, 2016; <doi:10.1016/j.csda.201502007>), and sparse least trimmed squares regression (Alfons, Croux & Gelper, 2013; <doi:10.1214/12-AOAS575>).

Version: 0.8.2

Depends: R (≥ 3.5.0), ggplot2 (≥ 0.9.2), perry (≥ 0.3.0), robustbase (≥ 0.9-5)

Imports: MASS, Rcpp (≥ 0.9.10), grDevices, parallel, stats, utils

LinkingTo: Rcpp (≥ 0.9.10), RcppArmadillo (≥ 0.7.200.1.0)

Suggests: lars, mvtnorm, testthat

Published: 2025年10月02日

DOI: 10.32614/CRAN.package.robustHD

Author: Andreas Alfons ORCID iD [aut, cre], Dirk Eddelbuettel [ctb]

Maintainer: Andreas Alfons <alfons at ese.eur.nl>

BugReports: https://github.com/aalfons/robustHD/issues

License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]

URL: https://github.com/aalfons/robustHD