Likelihood and Bayesian analysis of mixtures

被引：37

作者：

Aitkin, Murray ^{[1
,2
]}

机构：

[1] Univ Newcastle, Dept Stat, Newcastle Upon Tyne, Tyne & Wear, England

[2] Educ Stat Serv Inst, Washington, DC 20006 USA

来源：

STATISTICAL MODELLING | 2001年 / 1卷 / 04期

基金：

英国工程与自然科学研究理事会;

关键词：

Bayes; galaxy data; inference; Markov chain Monte Carlo; maximum likelihood; mixture model;

D O I：

10.1177/1471082X0100100404

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：

This paper compares likelihood and Bayesian analyses of finite mixture distributions, and expresses reservations about the latter. In particular, the role of prior assumptions in the full Monte Carlo Markov chain Bayes analysis is obscure, yet these assumptions clearly play a major role in the conclusions. These issues are illustrated with a detailed discussion of the well-known galaxy data.

引用

页码：287 / 304

页数：18

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