Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 289-306 |
| Number of pages | 18 |
| Journal | Journal of the Iranian Statistical Society |
| Volume | 20 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jun 1 2021 |
Bibliographical note
KAUST Repository Item: Exported on 2021-10-04Acknowledgements: 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.