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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 |
| Author: |
Klaus Nordhausen 
[aut, cre],
Aurore Archimbaud
[aut],
Anne Ruiz-Gazen
[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 |
Documentation:
Downloads:
Reverse dependencies:
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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.
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