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MOutliers  

Multivariate Outlier Detection Methods
View on CRAN: Click here


Download and install MOutliers package within the R console
Install from CRAN:
install.packages("MOutliers")

Install from Github:
library("remotes")
install_github("cran/MOutliers")

Install by package version:
library("remotes")
install_version("MOutliers", "0.1.2")



Attach the package and use:
library("MOutliers")
Maintained by
Senuri Yasara
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-06-16
Latest Update: 2026-06-16
Description:
Provides methods for detecting multivariate outliers in numeric datasets. The package implements classical Mahalanobis distance, robust Minimum Covariance Determinant (MCD), and Principal Component Analysis (PCA)-based approaches for outlier detection. The methodology is informed by Aggarwal (2017) <doi:10.1007/978-3-319-47578-3> and Grentzelos, Caroni and Barranco-Chamorro (2020) <doi:10.1002/cmm4.1129>. Visualization functions are included to aid interpretation of detected outliers. Mahalanobis distance calculations are accelerated using 'C++' through 'Rcpp'.
How to cite:
Senuri Yasara (2026). MOutliers: Multivariate Outlier Detection Methods. R package version 0.1.2, https://cran.r-project.org/web/packages/MOutliers. Accessed 06 Aug. 2026.
Previous versions and publish date:
0.1.1 (2026-06-15 14:00), (2026-07-09 08:09)
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Complete documentation for MOutliers
Functions, R codes and Examples using the MOutliers R package
Full MOutliers package functions and examples
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