ICSOutlier: Outlier Detection Using Invariant Coordinate Selection

Multivariate outlier detection is performed using invariant coordinates where the package offers different methods to choose the appropriate components. ICS is a general multivariate technique with many applications in multivariate analysis. ICSOutlier offers a selection of functions for automated detection of outliers in the data based on a fitted ICS object or by specifying the dataset and the scatters of interest. The current implementation targets data sets with only a small percentage of outliers.

Version: 0.4-0
Depends: R (≥ 3.0.0), methods, ICS (≥ 1.4-0), moments
Imports: graphics, grDevices, mvtnorm, parallel
Suggests: ICSClust, REPPlab, testthat (≥ 3.0.0)
Published: 2023-12-13
DOI: 10.32614/CRAN.package.ICSOutlier
Author: Klaus Nordhausen ORCID iD [aut, cre], Aurore Archimbaud ORCID iD [aut], Anne Ruiz-Gazen ORCID iD [aut]
Maintainer: Klaus Nordhausen <klausnordhausenR at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Citation: ICSOutlier citation info
Materials: NEWS
CRAN checks: ICSOutlier results


Reference manual: ICSOutlier.pdf


Package source: ICSOutlier_0.4-0.tar.gz
Windows binaries: r-devel: ICSOutlier_0.4-0.zip, r-release: ICSOutlier_0.4-0.zip, r-oldrel: ICSOutlier_0.4-0.zip
macOS binaries: r-release (arm64): ICSOutlier_0.4-0.tgz, r-oldrel (arm64): ICSOutlier_0.4-0.tgz, r-release (x86_64): ICSOutlier_0.4-0.tgz, r-oldrel (x86_64): ICSOutlier_0.4-0.tgz
Old sources: ICSOutlier archive

Reverse dependencies:

Reverse depends: ICSShiny
Reverse suggests: ICS, performance


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