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mvout  

Robust Multivariate Outlier Detection
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("mvout", "1.2")



Attach the package and use:
library("mvout")
Maintained by
Nathaniel E. Helwig
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-05-30
Latest Update: 2025-05-30
Description:
Detection of multivariate outliers using robust estimates of location and scale. The Minimum Covariance Determinant (MCD) estimator is used to calculate robust estimates of the mean vector and covariance matrix. Outliers are determined based on robust Mahalanobis distances using either an unstructured covariance matrix, a principal components structured covariance matrix, or a factor analysis structured covariance matrix. Includes options for specifying the direction of interest for outlier detection for each variable.
How to cite:
Nathaniel E. Helwig (2025). mvout: Robust Multivariate Outlier Detection. R package version 1.2, https://cran.r-project.org/web/packages/mvout. Accessed 21 Aug. 2026.
Previous versions and publish date:
No previous versions
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Complete documentation for mvout
Functions, R codes and Examples using the mvout R package
Full mvout package functions and examples
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