Robust Statistics: Theory and Methods

Companion package for the book: "Robust Statistics: Theory and Methods, second edition", <>. This package contains code that implements the robust estimators discussed in the recent second edition of the book above, as well as the scripts reproducing all the examples in the book.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


1.0.2 by Matias Salibian-Barrera, a year ago

Browse source code at

Authors: Matias Salibian-Barrera [cre] , Victor Yohai [aut] , Ricardo Maronna [aut] , Doug Martin [aut] , Gregory Brownson [aut] (ShinyUI) , Kjell Konis [aut] , Kjell Konis [cph] (erfi) , Christophe Croux [ctb] (WBYlogreg , BYlogreg) , Gentiane Haesbroeck [ctb] (WBYlogreg , BYlogreg) , Martin Maechler [cph] ( , , lmrob.S) , Manuel Koller [cph] ( , .vcov.avar1 , lmrob.S , lmrob.lar) , Matias Salibian-Barrera [aut]

Documentation:   PDF Manual  

GPL (>= 3) license

Imports stats, graphics, utils, methods, DEoptimR, pyinit, rrcov, robustbase, shiny, shinyjs, PerformanceAnalytics, DT, ggplot2, gridExtra, xts

Depends on fit.models

Suggests knitr, R.rsp

Imported by RPESE, RRBoost.

Suggested by PerformanceAnalytics, RBF, RPEIF.

See at CRAN