Robust Methods for High-Dimensional Data

AIC.seqModel | Information criteria for a sequence of regression models |

coefPlot | Coefficient plot of a sequence of regression models |

coef.seqModel | Extract coefficients from 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 |

fortify.seqModel | Convert a sequence of regression models into a data frame for... |

getScale | Extract the residual scale of a robust regression model |

grplars | (Robust) groupwise least angle regression |

lambda0 | Penalty parameter for sparse LTS regression |

perry.seqModel | Resampling-based prediction error for a sequential regression... |

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-deprecated | Deprecated functions in package 'robustHD' |

robustHD-package | Robust Methods for High-Dimensional Data |

sparseLTS | Sparse least trimmed squares regression |

standardize | Data standardization |

TopGear | Top Gear car data |

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... |

winsorize | Data cleaning by winsorization |

wt | Extract outlier weights from sparse LTS regression models |

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