Loading…

Modified AIC and Cp in multivariate linear regression

The Akaike information criterion, AIC, and the Mallows' Cp criterion have been proposed as approximately unbiased estimators for their risks or underlying criterion functions. In this paper we propose modified AIC and Cp, for selecting multivariate linear regression models. Our modified AIC and...

Full description

Saved in:
Bibliographic Details
Published in:Biometrika 1997-09, Vol.84 (3), p.707-716
Main Authors: FUJIKOSHI, YASUNORI, SATOH, KENICHI
Format: Article
Language:English
Subjects:
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The Akaike information criterion, AIC, and the Mallows' Cp criterion have been proposed as approximately unbiased estimators for their risks or underlying criterion functions. In this paper we propose modified AIC and Cp, for selecting multivariate linear regression models. Our modified AIC and modified Cp 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 Cp provide better approximations to their risk functions, and better model selection, than AIC and Cp.
ISSN:0006-3444
1464-3510
DOI:10.1093/biomet/84.3.707