On a Gibbs sampler based random process in Bayesian nonparametrics

被引：6

作者：

Favaro, Stefano ^{[1
,4
]}

Ruggiero, Matteo ^{[2
]}

Walker, Stephen G. ^{[3
]}

机构：

[1] Univ Turin, I-10134 Turin, Italy

[2] Univ Pavia, I-27100 Pavia, Italy

[3] Univ Kent, Canterbury CT2 7NZ, Kent, England

[4] Coll Carlo Alberto, Moncalieri, Italy

来源：

ELECTRONIC JOURNAL OF STATISTICS | 2009年 / 3卷

关键词：

Random probability measure; Dirichlet process; Blackwell-MacQueen Polya urn scheme; Gibbs sampler; Bayesian nonparametrics; FLEMING-VIOT PROCESS; CONSTRUCTIVE DEFINITION; DIRICHLET; DISTRIBUTIONS;

D O I：

10.1214/09-EJS563

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：

We define and investigate a new class of measure-valued Markov chains by resorting to ideas formulated in Bayesian nonparametrics related to the Dirichlet process and the Gibbs sampler. Dependent random probability measures in this class are shown to be stationary and ergodic with respect to the law of a Dirichlet process and to converge in distribution to the neutral diffusion model.

引用

页码：1556 / 1566

页数：11

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