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Robust model selection in regression via weighted likelihood methodology

✍ Scribed by Claudio Agostinelli

Publisher: Elsevier Science
Year: 2002
Tongue: English
Weight: 130 KB
Volume: 56
Category: Article
ISSN: 0167-7152
DOI: 10.1016/s0167-7152(01)00193-6

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✦ Synopsis

Robust model selection procedures are introduced as a robust modiÿcation of the Akaike information criterion (AIC) and Mallows Cp. These extensions are based on the weighted likelihood methodology. When the model is correctly speciÿed, these robust criteria are asymptotically equivalent to the classical ones under mild conditions. Robustness properties and the performance of the procedures are illustrated with examples and Monte Carlo simulations.

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