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Title: A comparison of robust versions of the AIC based on M, S and MM estimators
Authors: Tharmaratnam, Kukatharmini ×
Claeskens, Gerda #
Issue Date: 2013
Publisher: Gordon and Breach
Series Title: Statistics vol:47 issue:1 pages:216-235
Abstract: Variable selection in the presence of outliers may be performed by using a robust version of Akaike's information criterion (AIC). In this paper, explicit expressions are obtained for such criteria when S- and MM-estimators are used. The performance of these criteria is compared with the existing AIC based on M-estimators and with the classical non-robust AIC. In a simulation study and in data examples, we observe that the proposed AIC with S and MM-estimators selects more appropriate models in case outliers are present.
ISSN: 0233-1888
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
Leuven Statistics Research Centre (LStat)
× corresponding author
# (joint) last author

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