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robustHD (version 0.5.1)

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.

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Version

Install

install.packages('robustHD')

Monthly Downloads

2,037

Version

0.5.1

License

GPL (>= 2)

Maintainer

Andreas Alfons

Last Published

January 8th, 2016

Functions in robustHD (0.5.1)

predict.seqModel

Predict from a sequence of regression models
corHuber

Robust correlation based on winsorization.
standardize

Data standardization
grplars

(Robust) groupwise least angle regression
rlars

Robust least angle regression
winsorize

Data cleaning by winsorization
TopGear

Top Gear car data
plot.seqModel

Plot a sequence of regression models
fortify.seqModel

Convert a sequence of regression models into a data frame for plotting
tslarsP

(Robust) least angle regression for time series data with fixed lag length
coefPlot

Coefficient plot of a sequence of regression models
wt

Extract outlier weights from sparse LTS regression models
critPlot

Optimality criterion plot of a sequence of regression models
tsBlocks

Construct predictor blocks for time series models
fitted.seqModel

Extract fitted values from a sequence of regression models
robustHD-package

robustHD
robustHD-deprecated

Deprecated functions in package robustHD
AIC.seqModel

Information criteria for a sequence of regression models
residuals.seqModel

Extract residuals from a sequence of regression models
getScale

Extract the residual scale of a robust regression model
coef.seqModel

Extract coefficients from a sequence of regression models
perry.seqModel

Resampling-based prediction error for a sequential regression model
diagnosticPlot

Diagnostic plots for a sequence of regression models
lambda0

Penalty parameter for sparse LTS regression
sparseLTS

Sparse least trimmed squares regression
tslars

(Robust) least angle regression for time series data