MixMatrix: Classification with Matrix Variate Normal and t Distributions

Provides sampling and density functions for matrix variate normal, t, and inverted t distributions; ML estimation for matrix variate normal and t distributions using the EM algorithm, including some restrictions on the parameters; and classification by linear and quadratic discriminant analysis for matrix variate normal and t distributions described in Thompson et al. (2019) <doi:10.1080/10618600.2019.1696208>. Performs clustering with matrix variate normal and t mixture models.

Package overview README.md Discriminant Analysis for Matrix Variate Distributions Matrix Variate Mixture Models with the t distribution Matrix Variate Normal Distributions with MixMatrix ML estimation of the Matrix Variate t Distribution

Vignettes Man pages API and functions Files

Package details
Author	Geoffrey Thompson [aut, cre] (<https://orcid.org/0000-0003-2436-8822>), B. D. Ripley [ctb, cph] (author of original lda and qda functions), W. N. Venables [ctb, cph] (author of original lda and qda functions)
Maintainer	Geoffrey Thompson <gzthompson@gmail.com>
License	GPL-3
Version	0.2.8
URL	https://github.com/gzt/MixMatrix/ https://gzt.github.io/MixMatrix/
Package repository	View on CRAN
Installation	Install the latest version of this package by entering the following in R: `install.packages("MixMatrix")`