CerioliOutlierDetection: Outlier Detection Using the Iterated RMCD Method of Cerioli (2010)

Implements the iterated RMCD method of Cerioli (2010) for multivariate outlier detection via robust Mahalanobis distances. Also provides the finite-sample RMCD method discussed in the paper, as well as the methods provided in Hardin and Rocke (2005) <doi:10.1198/106186005X77685> and Green and Martin (2017).

Version: 1.1.13
Depends: R (≥ 4.0.0)
Imports: robustbase (≥ 0.91-1)
Suggests: rrcov, mvtnorm, mclust
Published: 2023-10-29
DOI: NA
Author: Christopher G. Green [aut, cre] (-7877), R. Doug Martin [ths]
Maintainer: Christopher G. Green <christopher.g.green at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://christopherggreen.github.io/CerioliOutlierDetection/
NeedsCompilation: no
Materials: README
CRAN checks: CerioliOutlierDetection results

Documentation:

Reference manual: CerioliOutlierDetection.pdf

Downloads:

Package source: CerioliOutlierDetection_1.1.13.tar.gz
Windows binaries: r-devel: CerioliOutlierDetection_1.1.13.zip, r-release: CerioliOutlierDetection_1.1.13.zip, r-oldrel: CerioliOutlierDetection_1.1.13.zip
macOS binaries: r-release (arm64): CerioliOutlierDetection_1.1.13.tgz, r-oldrel (arm64): CerioliOutlierDetection_1.1.13.tgz, r-release (x86_64): CerioliOutlierDetection_1.1.13.tgz, r-oldrel (x86_64): CerioliOutlierDetection_1.1.13.tgz
Old sources: CerioliOutlierDetection archive

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