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AbstractMatrix-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.
CitationNiekerk, J. van, Bekker, A., & Arashi, M. (2021). Matrix-Variate Beta Generator - Developments and Application. Journal of the Iranian Statistical Society, 20(1), 289–306. doi:10.52547/jirss.20.1.289
SponsorsThe 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.