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
收藏
页码：61 / 72
页数：12
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