# robustHD v0.6.1

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## Robust Methods for High-Dimensional Data

Robust methods for high-dimensional data, in particular linear model selection techniques based on least angle regression and sparse regression.

## Functions in robustHD

 Name Description fortify.seqModel Convert a sequence of regression models into a data frame for plotting TopGear Top Gear car data AIC.seqModel Information criteria for a sequence of regression models diagnosticPlot Diagnostic plots for a sequence of regression models critPlot Optimality criterion plot of a sequence of regression models corHuber Robust correlation based on winsorization. getScale Extract the residual scale of a robust regression model fitted.seqModel Extract fitted values from a sequence of regression models grplars (Robust) groupwise least angle regression robustHD-deprecated Deprecated functions in package robustHD tslarsP (Robust) least angle regression for time series data with fixed lag length tslars (Robust) least angle regression for time series data plot.seqModel Plot a sequence of regression models standardize Data standardization rlars Robust least angle regression perry.seqModel Resampling-based prediction error for a sequential regression model lambda0 Penalty parameter for sparse LTS regression tsBlocks Construct predictor blocks for time series models robustHD-package robustHD sparseLTS Sparse least trimmed squares regression weights.sparseLTS Extract outlier weights from sparse LTS regression models winsorize Data cleaning by winsorization coef.seqModel Extract coefficients from a sequence of regression models residuals.seqModel Extract residuals from a sequence of regression models predict.seqModel Predict from a sequence of regression models coefPlot Coefficient plot of a sequence of regression models No Results!