Finite Mixtures of Skewed Matrix Variate Distributions
Abstract
Clustering is the process of finding underlying group structures in data.
Although mixture model-based clustering is firmly established in the
multivariate case, there is a relative paucity of work on matrix variate
distributions and none for clustering with mixtures of skewed matrix variate
distributions. Four finite mixtures of skewed matrix variate distributions are
considered. Parameter estimation is carried out using an
expectation-conditional maximization algorithm, and both simulated and real
data are used for illustration.