数学
多元统计
贝叶斯多元线性回归
统计
一般线性模型
线性回归
多元分析
作者
Yasunori Fujikoshi,Kenichi Satoh
出处
期刊:Biometrika
[Oxford University Press]
日期:1997-09-01
卷期号:84 (3): 707-716
被引量:130
标识
DOI:10.1093/biomet/84.3.707
摘要
The Akaike information criterion, AIC, and the Mallows' C p criterion have been proposed as approximately unbiased estimators for their risks or underlying criterion functions. In this paper we propose modified AIC and C P , for selecting multivariate linear regression models. Our modified AIC and modified C p are intended to reduce bias in situations where the collection of candidate models includes both underspecified and overspecified models. In a simulation study it is verified that the modified AIC and modified C p provide better approximations to their risk functions, and better model selection, than AIC and C p .
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