ShapleyOutlier: Multivariate Outlier Explanations using Shapley Values and Mahalanobis Distances (original) (raw)
Based on Shapley values to explain multivariate outlyingness and to detect and impute cellwise outliers. Includes implementations of methods described in Mayrhofer and Filzmoser (2023) <doi:10.1016/j.ecosta.2023.04.003>.
| Version: | 0.1.2 |
|---|---|
| Depends: | R (≥ 4.0.0) |
| Imports: | dplyr, Rdpack, stats, tibble, tidyr, robustbase, forcats, egg, ggplot2, gridExtra, RColorBrewer, magrittr |
| Suggests: | grDevices, cellWise, robustHD, knitr, MASS, rmarkdown |
| Published: | 2024-10-17 |
| DOI: | 10.32614/CRAN.package.ShapleyOutlier |
| Author: | Marcus Mayrhofer [aut, cre], Peter Filzmoser [aut] |
| Maintainer: | Marcus Mayrhofer <marcus.mayrhofer at tuwien.ac.at> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Citation: | ShapleyOutlier citation info |
| In views: | AnomalyDetection |
| CRAN checks: | ShapleyOutlier results |
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