A semiparametric Bayesian model for randomised block designs

被引：215
作者：
Bush, CA [1 ]
MacEachern, SN [1 ]
机构：
[1] OHIO STATE UNIV,DEPT STAT,COLUMBUS,OH 43210
来源：
BIOMETRIKA | 1996年 / 83卷 / 02期
关键词：
Dirichlet process; Gibbs sampler; hierarchical model;
D O I：
10.1093/biomet/83.2.275
中图分类号：
Q [生物科学];
学科分类号：
07 ; 0710 ; 09 ;
摘要：
A model is proposed for a Bayesian semiparametric analysis of randomised block experiments. The model is a hierarchical model in which a Dirichlet process is inserted at the middle stage for the distribution of the block effects. This model allows an arbitrary distribution of block effects, and it results in effective estimates of treatment contrasts, block effects and the distribution of block effects. An effective computational strategy is presented for describing the posterior distribution.
引用
收藏
页码：275 / 285
页数：11
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