Bayesian models for sparse probability tables

被引：0

作者：

Smith, JQ ^{[1
]}

Queen, CM ^{[1
]}

机构：

[1] UNIV KENT,INST MATH & STAT,CANTERBURY CT2 7NZ,KENT,ENGLAND

来源：

ANNALS OF STATISTICS | 1996年 / 24卷 / 05期

关键词：

Bayesian probability estimation; constraint graph; contingency tables; decomposable graph; generalized Dirichlet distributions; separation of likelihood;

D O I：

暂无

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 wish to make inferences about the conditional probabilities p(y/x), many of which are zero, when the distribution of X is unknown and one observes only a multinomial sample of the Y variates. To do this, fixed likelihood ratio models and quasi-incremental distributions are defined. It is shown that quasi-incremental distributions are intimately linked to decomposable graphs and that these graphs can guide us to transformations of X and Y which admit a conjugate Bayesian analysis on a reparametrization of the conditional probabilities of interest.

引用

页码：2178 / 2198

页数：21

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