Skip navigation
Skip navigation

Asymptotic bootstrap corrections of AIC for linear regression models

Seghouane, Abd-Krim


The Akaike information criterion, AIC, and its corrected version, AICc are two methods for selecting normal linear regression models. Both criteria were designed as estimators of the expected Kullback-Leibler information between the model generating the data and the approximating candidate model. In this paper, two new corrected variants of AIC are derived for the purpose of small sample linear regression model selection. The proposed variants of AIC are based on asymptotic approximation of...[Show more]

CollectionsANU Research Publications
Date published: 2010
Type: Journal article
Source: Signal Processing
DOI: 10.1016/j.sigpro.2009.06.010


File Description SizeFormat Image
01_Seghouane_Asymptotic_bootstrap_2010.pdf228.77 kBAdobe PDF    Request a copy

Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  19 May 2020/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator