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outlierMBC  

Sequential Outlier Identification for Model-Based Clustering
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("outlierMBC", "0.0.1")



Attach the package and use:
library("outlierMBC")
Maintained by
Ultán P. Doherty
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-05-28
Latest Update: 2025-05-28
Description:
Sequential outlier identification for Gaussian mixture models using the distribution of Mahalanobis distances. The optimal number of outliers is chosen based on the dissimilarity between the theoretical and observed distributions of the scaled squared sample Mahalanobis distances. Also includes an extension for Gaussian linear cluster-weighted models using the distribution of studentized residuals. Doherty, McNicholas, and White (2025) <doi:10.48550/arXiv.2505.11668>.
How to cite:
Ultán P. Doherty (2025). outlierMBC: Sequential Outlier Identification for Model-Based Clustering. R package version 0.0.1, https://cran.r-project.org/web/packages/outlierMBC. Accessed 09 Oct. 2026.
Previous versions and publish date:
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Complete documentation for outlierMBC
Functions, R codes and Examples using the outlierMBC R package
Full outlierMBC package functions and examples
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