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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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Install
install.packages('robustHD')
Monthly Downloads
2,363
Version
0.5.1
License
GPL (>= 2)
Maintainer
Andreas Alfons
Last Published
January 8th, 2016
Functions in robustHD (0.5.1)
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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