Bayesian models for sparse probability tables

• 成果类型: Article
• 署名作者: Smith, JQ; Queen, CM
• 署名单位: University of Kent
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• 发表日期: 1996
• 页码: 2178-2198
• 关键词: categorical-data; hypergraphs; likelihood; inference; graphs

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.