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November 2016 Nonparametric Bayesian Clay for Robust Decision Bricks
Christian P. Robert, Judith Rousseau
Statist. Sci. 31(4): 506-510 (November 2016). DOI: 10.1214/16-STS567

Abstract

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.

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Christian P. Robert. Judith Rousseau. "Nonparametric Bayesian Clay for Robust Decision Bricks." Statist. Sci. 31 (4) 506 - 510, November 2016. https://doi.org/10.1214/16-STS567

Information

Published: November 2016
First available in Project Euclid: 19 January 2017

zbMATH: 06946242
MathSciNet: MR3598730
Digital Object Identifier: 10.1214/16-STS567

Rights: Copyright © 2016 Institute of Mathematical Statistics

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Vol.31 • No. 4 • November 2016
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