robustHD-package {robustHD}

Robust Methods for High-Dimensional Data

Description

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>).

Details

The DESCRIPTION file:

Package:	robustHD
Type:	Package
Title:	Robust Methods for High-Dimensional Data
Version:	0.8.0
Date:	2023-09-26
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 (>= 0.3.0)
Suggests:	lars, mvtnorm, testthat
Description:	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>).
License:	GPL (>= 2)
URL:	https://github.com/aalfons/robustHD
BugReports:	https://github.com/aalfons/robustHD/issues
LazyLoad:	yes
Authors@R:	c(person("Andreas", "Alfons", email = "[e-mail]", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-2513-3788")), person("Dirk", "Eddelbuettel", role = "ctb"))
Author:	Andreas Alfons [aut, cre] (<https://orcid.org/0000-0002-2513-3788>), Dirk Eddelbuettel [ctb]
Maintainer:	Andreas Alfons <[e-mail]>
Encoding:	UTF-8
RoxygenNote:	7.2.3

Index of help topics:

AIC.seqModel            Information criteria for a sequence of
                        regression models
TopGear                 Top Gear car data
coef.seqModel           Extract coefficients from a sequence of
                        regression models
coefPlot                Coefficient plot of a sequence of regression
                        models
corHuber                Robust correlation based on winsorization
critPlot                Optimality criterion plot of a sequence of
                        regression models
diagnosticPlot          Diagnostic plots for a sequence of regression
                        models
fitted.seqModel         Extract fitted values from a sequence of
                        regression models
getScale                Extract the residual scale of a robust
                        regression model
grplars                 (Robust) groupwise least angle regression
lambda0                 Penalty parameter for sparse LTS regression
nci60                   NCI-60 cancer cell panel
partialOrder            Find partial order of smallest or largest
                        values
perry.seqModel          Resampling-based prediction error for a
                        sequential regression model
plot.seqModel           Plot a sequence of regression models
predict.seqModel        Predict from a sequence of regression models
residuals.seqModel      Extract residuals from a sequence of regression
                        models
rlars                   Robust least angle regression
robustHD-package        Robust Methods for High-Dimensional Data
rstandard.seqModel      Extract standardized residuals from a sequence
                        of regression models
setupCoefPlot           Set up a coefficient plot of a sequence of
                        regression models
setupCritPlot           Set up an optimality criterion plot of a
                        sequence of regression models
setupDiagnosticPlot     Set up a diagnostic plot for a sequence of
                        regression models
sparseLTS               Sparse least trimmed squares regression
standardize             Data standardization
tsBlocks                Construct predictor blocks for time series
                        models
tslars                  (Robust) least angle regression for time series
                        data
tslarsP                 (Robust) least angle regression for time series
                        data with fixed lag length
weights.sparseLTS       Extract outlier weights from sparse LTS
                        regression models
winsorize               Data cleaning by winsorization

Author(s)

Andreas Alfons [aut, cre] (<https://orcid.org/0000-0002-2513-3788>), Dirk Eddelbuettel [ctb]

Maintainer: Andreas Alfons <[e-mail]>

References

Alfons (2021) robustHD: An R package for robust regression with high-dimensional data. Journal of Open Source Software, 6(67), 3786. doi:10.21105/joss.03786.