The bivariate Gauss hypergeometric beta distribution

被引：1

作者：

Nadarajah, Saralees ^{[1
]}

机构：

[1] Univ Manchester, Sch Math, Manchester, Lancs, England

来源：

INTEGRAL TRANSFORMS AND SPECIAL FUNCTIONS | 2008年 / 19卷 / 12期

关键词：

bivariate beta distribution; Fisher information matrix; Gauss hypergeometric function; maximum likelihood estimation;

D O I：

10.1080/10652460802149795

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

A new bivariate beta distribution based on the Gauss hypergeometric function is introduced. Various representations are derived for its product moments, marginal densities, marginal moments, conditional densities and conditional moments. The method of maximum likelihood is used to derive the associated estimation procedure as well as the Fisher information matrix.

引用

页码：859 / 868

页数：10

共 17 条

[1] Unified probability density function involving a confluent hypergeometric function of two variables [J].

Al-Saqabi, BN ;

Kalla, SL ;

Tuan, VK .

APPLIED MATHEMATICS AND COMPUTATION, 2003, 146 (01) :135-152

[2] A generalized inverse gaussian distribution with τ-confluent hypergeometric function [J].

Ali, I ;

Kalla, SL ;

Khajah, HG .

INTEGRAL TRANSFORMS AND SPECIAL FUNCTIONS, 2001, 12 (02) :101-114

[3]

[Anonymous], 1975, MODERN COURSE DISTRI

[4] THE FOUNDATIONS OF MODELS OF DEPENDENCE IN PROBABILISTIC SAFETY ASSESSMENT [J].

APOSTOLAKIS, G ;

MOIENI, P .

RELIABILITY ENGINEERING & SYSTEM SAFETY, 1987, 18 (03) :177-195

[5]

ARNOLD BC, 1999, CONDITIONAL SPECIFIC

[6]

Balakrishnan, 2000, CONTINUOUS MULTIVARI

[7]

GHITANY ME, 2002, INT J MATH SCI, V29, P727, DOI 10.1155/S0161171202106193

[8]

GRIVAS DA, 1982, J GEOTECH ENG DIV P, V108, P713

[9]

HOYER RW, 1976, 114 PRINC U DEP ST 2

[10]

Hutchinson T. P., 1991, ENG STATISTICIANS GU

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