Matrix-Variate Beta Generator - Developments and Application

نویسندگان

  • Andriette Bekke University of Pretoria, Department of Statistics, Pretoria, South Africa
  • Mohammad Arashi Ferdowsi University of Mashhad, Department of Statistics, Mashhad, Iran
چکیده مقاله:

Matrix-variate beta distributions are applied in different fields of hypothesis testing, multivariate correlation analysis, zero regression, canonical correlation analysis and etc. A methodology 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.

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عنوان ژورنال

دوره 20  شماره 1

صفحات  289- 306

تاریخ انتشار 2021-06

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