Author： Toma Aida
Publisher： MDPI
E-ISSN： 1099-4300|16|5|2686-2698
ISSN： 1099-4300
Source： Entropy, Vol.16, Iss.5, 2014-05, pp. : 2686-2698
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Abstract
In this note we introduce some divergence-based model selection criteria. These criteria are defined by estimators of the expected overall discrepancy between the true unknown model and the candidate model, using dual representations of divergences and associated minimum divergence estimators. It is shown that the proposed criteria are asymptotically unbiased. The influence functions of these criteria are also derived and some comments on robustness are provided.
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