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ShapleyOutlier
View on CRAN: Click
here
Download and install ShapleyOutlier package within the R console
Install from CRAN:
install.packages("ShapleyOutlier")
Install from Github:
library("remotes")
install_github("cran/ShapleyOutlier")
Install by package version:
library("remotes")
install_version("ShapleyOutlier", "0.1.2")
Attach the package and use:
library("ShapleyOutlier")
Maintained by
Marcus Mayrhofer
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-10-21
Latest Update: 2023-02-20
Description:
Based on Shapley values to explain multivariate outlyingness and to detect and impute cellwise outliers.
Includes implementations of methods described in Mayrhofer and Filzmoser (2022) .
How to cite:
Marcus Mayrhofer (2022). ShapleyOutlier: Multivariate Outlier Explanations using Shapley Values and Mahalanobis Distances. R package version 0.1.2, https://cran.r-project.org/web/packages/ShapleyOutlier. Accessed 04 Jan. 2025.
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Complete documentation for ShapleyOutlier
Functions, R codes and Examples using
the ShapleyOutlier R package
Some associated functions: MOE . SCD . ShapleyOutlier-package . WeatherVienna . new_shapley . new_shapley_algorithm . new_shapley_interaction . pipe . plot.shapley . plot.shapley_algorithm . plot.shapley_interaction . print.shapley . print.shapley_algorithm . print.shapley_interaction . shapley . shapley_interaction .
Some associated R codes: MOE.R . SCD.R . ShapleyOutlier-package.R . WeatherVienna.R . check_functions.R . classes.R . coordinate_correction.R . initial_estimates.R . min_MD.R . outlier_summary.R . plot_functions.R . shapley.R . shapley_base.R . shapley_interaction.R . utils-pipe.R . Full ShapleyOutlier package functions and examples
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