Home
Scholarly Works
Finite Mixtures of Skewed Matrix Variate...
Journal article

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.

Authors

Gallaugher MPB; McNicholas PD

Journal

, , ,

Publication Date

May 2, 2017

DOI

10.48550/arxiv.1703.08882

Labels

View published work (Non-McMaster Users)

Contact the Experts team