A Bayesian analysis of the Bingham distribution

被引：6

作者：

Walker, Stephen G. ^{[1
]}

机构：

[1] Univ Kent, Sch Math Stat & Actuarial Sci, Canterbury CT2 7NZ, Kent, England

来源：

BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS | 2014年 / 28卷 / 01期

关键词：

Latent variables; Markov chain Monte Carlo; normalizing constant; posterior distribution; MONTE-CARLO METHODS; NORMALIZING CONSTANT; GIBBS SAMPLER; COMPUTATION;

D O I：

10.1214/12-BJPS193

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

This paper provides a means, using latent variables, to undertake a Bayesian analysis for the Bingham distribution. To date, this has been problematic due to a nonclosed form for the normalizing constant. Previous approaches have relied on approximating the constant; something which is unnecessary in the method adopted here.

引用

页码：61 / 72

页数：12

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