Published by the Foundation for Open Access Statistics
Editors-in-chief: Bettina GrĂ¼n, Edzer Pebesma & Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Fast and Robust Bootstrap for Multivariate Inference: The R Package FRB | Van Aelst | Journal of Statistical Software
Authors: Stefan Van Aelst, Gert Willems
Title: Fast and Robust Bootstrap for Multivariate Inference: The R Package FRB
Abstract: We present the FRB package for R, which implements the fast and robust bootstrap. This method constitutes an alternative to ordinary bootstrap or asymptotic inference procedures when using robust estimators such as S-, MM- or GS-estimators. The package considers three multivariate settings: principal components analysis, Hotelling tests and multivariate regression. It provides both the robust point estimates and uncertainty measures based on the fast and robust bootstrap. In this paper we give some background on the method, discuss the implementation and provide various examples.

Page views:: 4416. Submitted: 2009-09-21. Published: 2013-04-21.
Paper: Fast and Robust Bootstrap for Multivariate Inference: The R Package FRB     Download PDF (Downloads: 4791)
Supplements:
FRB_1.8.tar.gz: R source package Download (Downloads: 430; 90KB)
v53i03.R: R example code from the paper Download (Downloads: 409; 2KB)

DOI: 10.18637/jss.v053.i03

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.