文章基本信息

标题：Bivariate Beta and Kumaraswamy models with independent gamma components
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作者：Barry C. Arnold ; Indranil Ghosh.
期刊名称：RevStat : Statistical Journal
印刷版ISSN：1645-6726
出版年度：2017
卷号：15
期号：2
页码：223-250
出版社：Instituto Nacional de Estatística
摘要：In this paper, we consider a general framework for constructing new valid densitiesregarding a random matrix variate. However, we focus specically on the Wishartdistribution. The methodology involves coupling the density function of the Wishartdistribution with a Borel measurable function as a weight. We propose three dierentweights by considering trace and determinant operators on matrices. The charac-teristics for the proposed weighted-type Wishart distributions are studied and theenrichment of this approach is illustrated. A special case of this weighted-type dis-tribution is applied in the Bayesian analysis of the normal model in the univariateand multivariate cases. It is shown that the performance of this new prior model iscompetitive using various measures.
关键词：Bayesian analysis; eigenvalues; Kummer gamma; Kummer Wishart; matrix variate;weight function; Wishart distribution.