The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

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 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

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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=FRB to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.