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Entropy 2014, 16(5), 2686-2698; doi:10.3390/e16052686

Model Selection Criteria Using Divergences

1 Department of Applied Mathematics, Bucharest Academy of Economic Studies, Piaṱa Romană 6, Bucharest, 010374, Romania 2 Gh. Mihoc-C. Iacob" Institute of Mathematical Statistics and Applied Mathematics,Romanian Academy, Calea 13 Septembrie 13, Bucharest, 050711, Romania 
Received: 1 April 2014 / Revised: 12 May 2014 / Accepted: 13 May 2014 / Published: 14 May 2014


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.
Keywords: divergence measure; duality; model selection divergence measure; duality; model selection
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Toma, A. Model Selection Criteria Using Divergences. Entropy 2014, 16, 2686-2698.

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