Some comments about James Watson's and Chris Holmes' "Approximate Models and Robust Decisions": Nonparametric Bayesian clay for robust decision bricks
Methodology
2016-04-12 v2 Computation
Abstract
This note discusses Watson and Holmes (2016) and their pro- posals towards more robust Bayesian decisions. While we acknowledge and commend the authors for setting new and all-encompassing prin- ciples 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 de- cisions. We also wonder at the ultimate relevance of Kullback-Leibler neighbourhoods to characterise robustness and favour extensions along non-parametric axes.
Keywords
Cite
@article{arxiv.1603.09088,
title = {Some comments about James Watson's and Chris Holmes' "Approximate Models and Robust Decisions": Nonparametric Bayesian clay for robust decision bricks},
author = {Christian P. Robert and Judith Rousseau},
journal= {arXiv preprint arXiv:1603.09088},
year = {2016}
}
Comments
7 pages, discussion of Watson and Holmes (2016) to appear in Statistical Science