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

Model Selection Criteria Using Divergences

Received: 1 April 2014 / Revised: 12 May 2014 / Accepted: 13 May 2014 / Published: 14 May 2014
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.
Keywords: divergence measure; duality; model selection divergence measure; duality; model selection
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

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

AMA Style

Toma A. Model Selection Criteria Using Divergences. Entropy. 2014; 16(5):2686-2698.

Chicago/Turabian Style

Toma, Aida. 2014. "Model Selection Criteria Using Divergences." Entropy 16, no. 5: 2686-2698.

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