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MatrixMixtures  

Model-Based Clustering via Matrix-Variate Mixture Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("MatrixMixtures", "1.0.0")



Attach the package and use:
library("MatrixMixtures")
Maintained by
Michael P.B. Gallaugher
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-06-11
Latest Update: 2021-06-11
Description:
Implements finite mixtures of matrix-variate contaminated normal distributions via expectation conditional-maximization algorithm for model-based clustering, as described in Tomarchio et al.(2020) . One key advantage of this model is the ability to automatically detect potential outlying matrices by computing their a posteriori probability of being typical or atypical points. Finite mixtures of matrix-variate t and matrix-variate normal distributions are also implemented by using expectation-maximization algorithms.
How to cite:
Michael P.B. Gallaugher (2021). MatrixMixtures: Model-Based Clustering via Matrix-Variate Mixture Models. R package version 1.0.0, https://cran.r-project.org/web/packages/MatrixMixtures. Accessed 30 Oct. 2026.
Previous versions and publish date:
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Complete documentation for MatrixMixtures
Functions, R codes and Examples using the MatrixMixtures R package
Some associated functions: MatrixMixt . SimX . 
Some associated R codes: MVCN.R . MVN.R . MVT.R . Main.R . Others.R . SimX.R .  Full MatrixMixtures package functions and examples
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