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: CerioliOutlierDetection_1.1.9.tgz, r-oldrel: CerioliOutlierDetection_1.1.9.tgz |
Old sources: | CerioliOutlierDetection archive |
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