Using principal component analysis as a base model, 'SCOUTer' offers a new approach to simulate outliers in a simple and precise way. The user can generate new observations defining them by a pair of well-known statistics: the Squared Prediction Error (SPE) and the Hotelling's T^2 (T^2) statistics. Just by introducing the target values of the SPE and T^2, 'SCOUTer' returns a new set of observations with the desired target properties. Authors: Alba González, Abel Folch-Fortuny, Francisco Arteaga and Alberto Ferrer (2020).
| Version: | 1.0.0 |
| Depends: | R (≥ 3.5.0),ggplot2,ggpubr, stats |
| Suggests: | knitr,rmarkdown |
| Published: | 2020-06-30 |
| DOI: | 10.32614/CRAN.package.SCOUTer |
| Author: | Alba Gonzalez Cebrian [aut, cre], Abel Folch-Fortuny [aut], Francisco Arteaga [aut], Alberto Ferrer [aut] |
| Maintainer: | Alba Gonzalez Cebrian <algonceb at upv.es> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README |
| In views: | AnomalyDetection |
| CRAN checks: | SCOUTer results |
| Reference manual: | SCOUTer.html ,SCOUTer.pdf |
| Vignettes: | SCOUTer demo (source,R code) |
| Package source: | SCOUTer_1.0.0.tar.gz |
| Windows binaries: | r-devel:SCOUTer_1.0.0.zip, r-release:SCOUTer_1.0.0.zip, r-oldrel:SCOUTer_1.0.0.zip |
| macOS binaries: | r-release (arm64):SCOUTer_1.0.0.tgz, r-oldrel (arm64):SCOUTer_1.0.0.tgz, r-release (x86_64):SCOUTer_1.0.0.tgz, r-oldrel (x86_64):SCOUTer_1.0.0.tgz |
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