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Nonparametric Bayesian Clay for Robust Decision Bricks

Robert, Christian P.; Rousseau, Judith (2016), Nonparametric Bayesian Clay for Robust Decision Bricks, Statistical Science, 31, 4, p. 506-510. 10.1214/16-STS567

Type
Article accepté pour publication ou publié
External document link
https://arxiv.org/abs/1603.09088
Date
2016
Journal name
Statistical Science
Volume
31
Number
4
Pages
506-510
Publication identifier
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Author(s)
Robert, Christian P.
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Rousseau, Judith
CEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
Abstract (EN)
his 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.
Subjects / Keywords
decision-theory; prior selection; robust methodology; misspecification