MATRIX-VARIATE GAUSS HYPERGEOMETRIC DISTRIBUTION

被引：5

作者：

Gupta, Arjun K. ^{[1
]}

Nagar, Daya K. ^{[2
]}

机构：

[1] Bowling Green State Univ, Dept Math & Stat, Bowling Green, OH 43403 USA

[2] Univ Antioquia, Inst Matemat, Medellin, Colombia

来源：

JOURNAL OF THE AUSTRALIAN MATHEMATICAL SOCIETY | 2012年 / 92卷 / 03期

关键词：

beta distribution; beta function; gamma function; invariant polynomial; matrix-variate; transformation; zonal polynomial; LATENT ROOTS;

D O I：

10.1017/S1446788712000353

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

In this paper, we propose a matrix-variate generalization of the Gauss hypergeometric distribution and study several of its properties. We also derive probability density functions of the product of two independent random matrices when one of them is Gauss hypergeometric. These densities are expressed in terms of Appell's first hypergeometric function F-1 and Humbert's confluent hypergeometric function Phi(1) of matrix arguments.

引用

页码：335 / 355

页数：21

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