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Nonparametric Bayesian Clay for Robust Decision Bricks

delete2016-11-01
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OA
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C
Christian P. Robert *
J
Judith Rousseau
DOI:10.1214/16-STS567delete
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Abstract

Abstract

En 中文
This note discusses Watson and Holmes [Statist. Sci. (2016) 31 465-489] and their proposals towards more robust Bayesian decisions. While we acknowledge and commend the authors for setting new and all encompassing principles of Bayesian robustness, and while we appreciate the strong anchoring of these within a decision-theoretic framework, we remain uncertain as to what extent such principles can be applied outside binary decisions. We also wonder at the ultimate relevance of Kullback-Leibler neighbourhoods into characterising robustness and we instead favour extensions along nonparametric axes.
Keywords:
Decision-theory
Gamma-minimaxity
misspecification
prior selection
robust methodology
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Statistical Science cover
Statistical Science
IF:
3.4
Papers:
1.0K
Citations:
8.7K

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U
Universite PSL
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3.3W
Papers: 2.5W
Citations: 91