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: 1.1.9
Depends: R (≥ 3.0.0)
Imports: robustbase (≥ 0.91-1)
Suggests: rrcov, robust, mvtnorm, alr3
Published: 2017-07-25
Author: Christopher G. Green [aut, cre], R. Doug Martin [ths]
Maintainer: Christopher G. Green <christopher.g.green at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://christopherggreen.github.io/CerioliOutlierDetection/
NeedsCompilation: no
Materials: README
CRAN checks: CerioliOutlierDetection results


Reference manual: CerioliOutlierDetection.pdf


Package source: CerioliOutlierDetection_1.1.9.tar.gz
Windows binaries: r-devel: CerioliOutlierDetection_1.1.9.zip, r-release: CerioliOutlierDetection_1.1.9.zip, r-oldrel: CerioliOutlierDetection_1.1.9.zip
macOS binaries: r-release (arm64): CerioliOutlierDetection_1.1.9.tgz, r-oldrel (arm64): CerioliOutlierDetection_1.1.9.tgz, r-release (x86_64): CerioliOutlierDetection_1.1.9.tgz, r-oldrel (x86_64): CerioliOutlierDetection_1.1.9.tgz
Old sources: CerioliOutlierDetection archive


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