CRAN/E | robustHD

robustHD

Robust Methods for High-Dimensional Data

Installation

About

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).

Citation robustHD citation info
github.com/aalfons/robustHD
Bug report File report

Key Metrics

Version 0.8.0
R ≥ 3.5.0
Published 2023-09-26 218 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks robustHD results

Downloads

Yesterday 80 -27%
Last 7 days 578 -20%
Last 30 days 2.263 -3%
Last 90 days 6.496 -30%
Last 365 days 30.614 -33%

Maintainer

Maintainer

Andreas Alfons

alfons@ese.eur.nl

Authors

Andreas Alfons

aut / cre

Dirk Eddelbuettel

ctb

Material

NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

robustHD archive

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

Suggests

lars
mvtnorm
testthat

LinkingTo

Rcpp ≥ 0.9.10
RcppArmadillo ≥ 0.3.0

Reverse Depends

sparseLTSEigen

Reverse Imports

enetLTS
gamreg
PAMhm
robCompositions
rrcovHD

Reverse Suggests

cellWise
ShapleyOutlier