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). Performs clustering with matrix variate normal and t mixture models.