A note on the unification of the Akaike information criterion

P. Shi and C‐L. Tsai

Journal of the Royal Statistical Society Series B, 1998, vol. 60, issue 3, 551-558

Abstract: To measure the distance between a robust function evaluated under the true regression model and under a fitted model, we propose generalized Kullback–Leibler information. Using this generalization we have developed three robust model selection criteria, AICR*, AICCR* and AICCR, that allow the selection of candidate models that not only fit the majority of the data but also take into account non‐normally distributed errors. The AICR* and AICCR criteria can unify most existing Akaike information criteria; three examples of such unification are given. Simulation studies are presented to illustrate the relative performance of each criterion.

Date: 1998
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