TopGear dataset | Explaining multivariate outlyingness | Analyzing cellwise outliers | Shapley interaction indices | WeatherVienna | Iterations of SCD and MOE for the year 2021
Package: ShapleyOutlier 0.1.2
ShapleyOutlier: Multivariate Outlier Explanations using Shapley Values and Mahalanobis Distances
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>.
Authors:
ShapleyOutlier_0.1.2.tar.gz
ShapleyOutlier_0.1.2.zip(r-4.7)ShapleyOutlier_0.1.2.zip(r-4.6)ShapleyOutlier_0.1.2.zip(r-4.5)
ShapleyOutlier_0.1.2.tgz(r-4.6-any)ShapleyOutlier_0.1.2.tgz(r-4.5-any)
ShapleyOutlier_0.1.2.tar.gz(r-4.7-any)ShapleyOutlier_0.1.2.tar.gz(r-4.6-any)
ShapleyOutlier_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
ShapleyOutlier/json (API)
| # Install 'ShapleyOutlier' in R: |
| install.packages('ShapleyOutlier', repos = c('https://marcusmayrhofer.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- WeatherVienna - Weather data from Vienna
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:cab0c34f93. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 150 | ||
| source / vignettes | OK | 231 | ||
| linux-release-x86_64 | OK | 138 | ||
| macos-release-arm64 | OK | 158 | ||
| macos-oldrel-arm64 | OK | 192 | ||
| windows-devel | OK | 116 | ||
| windows-release | OK | 102 | ||
| windows-oldrel | OK | 108 | ||
| wasm-release | OK | 341 |
Exports:%>%MOEnew_shapleynew_shapley_algorithmnew_shapley_interactionSCDshapleyshapley_interaction
Dependencies:clicpp11DEoptimRdplyreggfarverforcatsgenericsggplot2gluegridExtragtableisobandlabelinglifecyclemagrittrpillarpkgconfigpurrrR6rbibutilsRColorBrewerRdpackrlangrobustbaseS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Detecting cellwise outliers using Shapley values based on local outlyingness. | MOE |
| Class constructor for class 'shapley'. | new_shapley |
| Class constructor for class 'shapley_algorithm'. | new_shapley_algorithm |
| Class constructor for class 'shapley_interaction'. | new_shapley_interaction |
| Barplot of Shapley values | plot.shapley |
| Barplot and tileplot of Shapley values. | plot.shapley_algorithm |
| Plot of Shapley interaction indices | plot.shapley_interaction |
| Print function for class 'shapley'. | print.shapley |
| Print function for class 'shapley_algorithm'. | print.shapley_algorithm |
| Print function for class 'shapley_interaction'. | print.shapley_interaction |
| Detecting cellwise outliers using Shapley values. | SCD |
| Decomposition of squared Mahalanobis distance using Shapley values. | shapley |
| Decomposition of squared Mahalanobis distance using Shapley interaction indices. | shapley_interaction |
| Weather data from Vienna | WeatherVienna |
