Matrix-variate beta distributions are applied in different fields of hypothesis testing, multivariate correlation analysis, zero regression, canonical correlation analysis and etc. Amethodology is proposed to generate matrix-variate beta generator distributions by combining the matrix-variate beta kernel with an unknown function of the trace operator. Several statistical characteristics, extensions and developments are presented. Special members are then used in a univariate and multivariate Bayesian analysis setting. These models are fitted to simulated and real datasets, and their fitting and performance are compared to well-established competitors.
Bibliographical noteKAUST Repository Item: Exported on 2021-10-04
Acknowledgements: The authors would like to hereby acknowledge the support of the StatDisT group. This work is based upon research supported by the National Research foundation of South Africa, Reference: SRUG 190308422768 grant number 120839, IFR170227223754 grant number 109214 and SARCHI Research Chair UID: 71199. The opinions expressed and conclusions arrived at are those of the authors and are not necessarily to be attributed to the NRF.