Minimum Description Length Methods in Bayesian Model Selection: Some Applications

• 作者: Mohan Delampady
• 来源期刊: 统计学期刊(英文)
• 学科: 医学
• 关键词: BAYESIAN Analysis Model Selection Minimum DESCRIPTION LENGTH HIERARCHICAL BAYES BAYESIAN COMPUTATIONS
• 年，卷（期）: 2013,（2）
• 页码范围: 103-117
• 页数: 15页
• 分类号: R73

摘要

Computations involved in Bayesian approach to practical model selection problems are usually very difficult. Computational simplifications are sometimes possible, but are not generally applicable. There is a large literature available on a methodology based on information theory called Minimum Description Length (MDL). It is described here how many of these techniques are either directly Bayesian in nature, or are very good objective approximations to Bayesian solutions. First, connections between the Bayesian approach and MDL are theoretically explored;thereafter a few illustrations are provided to describe how MDL can give useful computational simplifications.