On the consistency and the robustness in model selection criteria |
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Authors: | Sumito Kurata Etsuo Hamada |
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Affiliation: | 1. Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka, Japan;2. Department of Mathematical Informatics, Tokyo University, Tokyo, Japankurata@mist.i.u-tokyo.ac.jp |
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Abstract: | AbstractIn the model selection problem, the consistency of the selection criterion has been often discussed. This paper derives a family of criteria based on a robust statistical divergence family by using a generalized Bayesian procedure. The proposed family can achieve both consistency and robustness at the same time since it has good performance with respect to contamination by outliers under appropriate circumstances. We show the selection accuracy of the proposed criterion family compared with the conventional methods through numerical experiments. |
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Keywords: | Model selection BHHJ divergence influence function consistency robustness |
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