Methods and criteria for model selection

被引:267
作者
Kadane, JB [1 ]
Lazar, NA [1 ]
机构
[1] Carnegie Mellon Univ, Dept Stat, Pittsburgh, PA 15213 USA
关键词
AIC; Bayes factors; BIC; Mallow's C-p; model averaging; subset selection; variable selection;
D O I
10.1198/016214504000000269
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
Model selection is an important part of any statistical analysis and, indeed, is central to the pursuit of science in general. Many authors have examined the question of model selection from both frequentist and Bayesian perspectives, and many tools for selecting the "best model" have been suggested in the literature. This paper considers the various proposals from a Bayesian decision-theoretic perspective.
引用
收藏
页码:279 / 290
页数:12
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