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robustHD (version 0.3.2)
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
0.3.2
License
GPL (>= 2)
Maintainer
Andreas Alfons
Last Published
May 2nd, 2013
Functions in robustHD (0.3.2)
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robustHD-package
Robust methods for high-dimensional data
robustHD-deprecated
Deprecated functions in package
robustHD
fortify.seqModel
Convert a sequence of regression models into a data frame for plotting
standardize
Data standardization
sparseLTS
Sparse least trimmed squares regression
rlars
Robust least angle regression
lambda0
Penalty parameter for sparse LTS regression
AIC.seqModel
Information criteria for a sequence of regression models
wt
Extract outlier weights from sparse LTS regression models
coef.seqModel
Extract coefficients from a sequence of regression models
coefPlot
Coefficient plot of a sequence of regression models
plot.seqModel
Plot a sequence of regression models
critPlot
Optimality criterion plot of a sequence of regression models
winsorize
Data cleaning by winsorization
diagnosticPlot
Diagnostic plots for a sequence of regression models
fitted.seqModel
Extract fitted values from a sequence of regression models
perry.seqModel
Resampling-based prediction error for a sequential regression model
residuals.seqModel
Extract residuals from a sequence of regression models
getScale
Extract the residual scale of a robust regression model
predict.seqModel
Predict from a sequence of regression models
corHuber
Robust correlation based on winsorization.