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.">

FRB: Fast and Robust Bootstrap (original) (raw)

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 ORCID iD [cre]
Maintainer: Valentin Todorov <valentin.todorov at chello.at>
License: GPL (≥ 3)
NeedsCompilation: no
Citation: FRB citation info
Materials: NEWS
CRAN checks: FRB results

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