FRB: Fast and Robust Bootstrap

Perform robust inference based on applying Fast and Robust Bootstrap on robust estimators (Van Aelst and Willems (2013) <doi:10.18637/jss.v053.i03>). This method constitutes an alternative to ordinary bootstrap or asymptotic inference. procedures when using robust estimators such as S-, MM- or GS-estimators. The available methods are multivariate regression, principal component analysis and one-sample and two-sample Hotelling tests. It provides both the robust point estimates and uncertainty measures based on the fast and robust bootstrap.

Version:	2.0-1
Depends:	R (≥ 2.10)
Imports:	rrcov, corpcor
Suggests:	robustbase
Published:	2024-10-07
DOI:	10.32614/CRAN.package.FRB
Author:	Ella Roelant [aut], Stefan Van Aelst [aut], Gert Willems [aut], Valentin Todorov [cre]
Maintainer:	Valentin Todorov <valentin.todorov at chello.at>
License:	GPL (≥ 3)
NeedsCompilation:	no
Citation:	FRB citation info
Materials:	NEWS
CRAN checks:	FRB results

Documentation:

Reference manual:

FRB.pdf

Downloads:

Package source:	FRB_2.0-1.tar.gz
Windows binaries:	r-devel: FRB_2.0-1.zip, r-release: FRB_2.0-1.zip, r-oldrel: FRB_2.0-1.zip
macOS binaries:	r-release (arm64): FRB_2.0-1.tgz, r-oldrel (arm64): FRB_2.0-1.tgz, r-release (x86_64): FRB_2.0-1.tgz, r-oldrel (x86_64): FRB_2.0-1.tgz
Old sources:	FRB archive

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