Multivariate Outlier Explanations using Shapley Values and Mahalanobis Distances R package ShapleyOutlier version 0.1.2 CRAN Task View: AnomalyDetection (https://CRAN.R-project.org/view=AnomalyDetection) 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>. Software 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 Marcus Mayrhofer <marcus.mayrhofer@tuwien.ac.at> Comprehensive R Archive Network (CRAN) Marcus Mayrhofer [aut, cre], Peter Filzmoser [aut] GPL-3 2024-10-17 application/tgz https://CRAN.R-project.org/package=ShapleyOutlier doi:10.32614/CRAN.package.ShapleyOutlier