Reference

Package Introduction

MixMatrix MixMatrix-package

Classification with Matrix Variate Normal and t Distributions

Distributions

Sampling and density functions for matrix variate distributions

rmatrixnorm() dmatrixnorm()

Matrix variate Normal distribution functions

rmatrixt() dmatrixt()

Distribution functions for the matrix variate t distribution.

rmatrixinvt() dmatrixinvt()

Distribution functions for matrix variate inverted t distributions

Maximum Likelihood Estimation

Maximum likelihood estimation for the normal and t distribution

MLmatrixnorm()

Maximum likelihood estimation for matrix normal distributions

MLmatrixt()

Maximum likelihood estimation for matrix variate t distributions

matrixmixture()

Fit a matrix variate mixture model

init_matrixmixture()

Initializing settings for Matrix Mixture Models

Discriminant Analysis

Linear and quadratic discriminant analysis

matrixlda()

LDA for matrix variate distributions

matrixqda()

Quadratic Discriminant Analysis for Matrix Variate Observations

predict(<matrixlda>)

Classify Matrix Variate Observations by Linear Discrimination

predict(<matrixqda>)

Classify Matrix Variate Observations by Quadratic Discrimination

Accessory functions

ARgenerate()

Generate a unit AR(1) covariance matrix

CSgenerate()

Generate a compound symmetric correlation matrix