线性模型下基于AIC准则的Bayes变量选择

Bayesian variable selection based on AIC criteria in linear models

讨论了线性模型下Bayes变量选择问题。通过用AIC准则来修正经典的Bayes变量选择方法,构造修正后的子模型后验分布,并且通过仿真计算验证,修正后的后验分布可以提高变量选择精度。

The problem of Bayesian variable selection in linear models is studied.Different from the classical method of Bayesian variable selection,AIC criteria is used to construct the posterior distribution of the subset model.Simulation studies are also provided to demonstrate the better performance of the proposed method.