Robust Methods for High-Dimensional Data R package robustHD version 0.8.4 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.2015.02.007>), and sparse least trimmed squares regression (Alfons, Croux & Gelper, 2013; <doi:10.1214/12-AOAS575>). Software 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, rlang, stats, utils LinkingTo: Rcpp (>= 0.9.10), RcppArmadillo (>= 0.7.200.1.0) Suggests: lars, mvtnorm, testthat Andreas Alfons <alfons@ese.eur.nl> Comprehensive R Archive Network (CRAN) Andreas Alfons [aut, cre] (ORCID: <https://orcid.org/0000-0002-2513-3788>), Dirk Eddelbuettel [ctb] GPL (>= 2) 2026-01-20 application/tgz https://CRAN.R-project.org/package=robustHD doi:10.32614/CRAN.package.robustHD