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Article Dans Une Revue Statistical Science Année : 2017

Nonparametric Bayesian Clay for Robust Decision Bricks

Résumé

This note discusses Watson and Holmes (2016) 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 we appreciate the strong anchoring of those within a decision-theoretic referential, we remain uncertain as to which extent such principles can be applied outside binary decisions. We also wonder at the ultimate relevance of Kullback-Leibler neighbourhoods to characterise robustness and favour extensions along non-parametric axes.

Dates et versions

hal-01517665 , version 1 (03-05-2017)

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Christian Robert, Judith J. Rousseau. Nonparametric Bayesian Clay for Robust Decision Bricks. Statistical Science, 2017, ⟨10.1214/16-STS567⟩. ⟨hal-01517665⟩
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