Fast and Robust Bootstrap for Multivariate Inference: The R Package FRB

被引:0
|
作者
Van Aelst, Stefan [1 ]
Willems, Gert [1 ]
机构
[1] Univ Ghent, Dept Appl Math & Comp Sci, B-9000 Ghent, Belgium
来源
JOURNAL OF STATISTICAL SOFTWARE | 2013年 / 53卷 / 03期
关键词
robustness; multivariate regression; principal components analysis; Hotelling tests; outliers; GENERALIZED S-ESTIMATORS; REGRESSION;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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.
引用
收藏
页码:1 / 32
页数:32
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