Package: MOutliers 0.0.0.9000

Senuri Yasara

MOutliers: Multivariate Outlier Detection Methods

Provides tools for detecting multivariate outliers in numeric datasets using Mahalanobis distance, robust Minimum Covariance Determinant (MCD), and Principal Component Analysis (PCA)-based methods. The Mahalanobis distance calculations are performed using an efficient C++ backend via Rcpp.

Authors:Senuri Yasara [aut, cre]

MOutliers_0.0.0.9000.tar.gz
MOutliers_0.0.0.9000.zip(r-4.7)MOutliers_0.0.0.9000.zip(r-4.6)MOutliers_0.0.0.9000.zip(r-4.5)
MOutliers_0.0.0.9000.tgz(r-4.6-x86_64)MOutliers_0.0.0.9000.tgz(r-4.6-arm64)MOutliers_0.0.0.9000.tgz(r-4.5-x86_64)MOutliers_0.0.0.9000.tgz(r-4.5-arm64)
MOutliers_0.0.0.9000.tar.gz(r-4.7-arm64)MOutliers_0.0.0.9000.tar.gz(r-4.7-x86_64)MOutliers_0.0.0.9000.tar.gz(r-4.6-arm64)MOutliers_0.0.0.9000.tar.gz(r-4.6-x86_64)
MOutliers_0.0.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
MOutliers/json (API)

# Install 'MOutliers' in R:
install.packages('MOutliers', repos = c('https://senuyasara.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/senuyasara/multivariate_outlier_detection_r_package/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cpp

4.40 score 2 exports 21 dependencies

Last updated from:1756e36792. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK172
linux-devel-x86_64OK150
source / vignettesOK263
linux-release-arm64OK154
linux-release-x86_64OK148
macos-release-arm64OK156
macos-release-x86_64OK304
macos-oldrel-arm64OK208
macos-oldrel-x86_64OK335
windows-develOK132
windows-releaseOK145
windows-oldrelOK117
wasm-releaseOK106

Exports:detect_multivariate_outliersplot_outliers

Dependencies:clicowplotcpp11farverggplot2gluegridExtragtableisobandlabelinglifecycleMASSR6RColorBrewerRcpprlangS7scalesvctrsviridisLitewithr

Multivariate Outlier Detection

Rendered frommultivariate_outliers.Rmdusingknitr::rmarkdownon Jun 16 2026.

Last update: 2025-10-22
Started: 2025-09-26

Readme and manuals

Help Manual

Help pageTopics
Detect Multivariate Outliersdetect_multivariate_outliers
Plot Pairwise Outliersplot_outliers