Optimal alternative robustness in Bayesian Decision Theory.

Fabrizio Ruggeri; Jacinto Martín; David Ríos Insua

RACSAM (2003)

  • Volume: 97, Issue: 3, page 407-412
  • ISSN: 1578-7303

Abstract

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In Martin et al (2003), we suggested an approach to general robustness studies in Bayesian Decision Theory and Inference, based on ε-contamination neighborhoods. In this note, we generalise the results considering neighborhoods based on norms, specifically, the supremum norm for utilities and the total variation norm for probability distributions. We provide tools to detect changes in preferences between alternatives under perturbations of the prior and/or the utility and the most sensitive direction.

How to cite

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Ruggeri, Fabrizio, Martín, Jacinto, and Ríos Insua, David. "Optimal alternative robustness in Bayesian Decision Theory.." RACSAM 97.3 (2003): 407-412. <http://eudml.org/doc/40988>.

@article{Ruggeri2003,
abstract = {In Martin et al (2003), we suggested an approach to general robustness studies in Bayesian Decision Theory and Inference, based on ε-contamination neighborhoods. In this note, we generalise the results considering neighborhoods based on norms, specifically, the supremum norm for utilities and the total variation norm for probability distributions. We provide tools to detect changes in preferences between alternatives under perturbations of the prior and/or the utility and the most sensitive direction.},
author = {Ruggeri, Fabrizio, Martín, Jacinto, Ríos Insua, David},
journal = {RACSAM},
keywords = {Decisión bayesiana; Robustez; sensitivity analysis; class of utilities; class of priors; dominance},
language = {eng},
number = {3},
pages = {407-412},
title = {Optimal alternative robustness in Bayesian Decision Theory.},
url = {http://eudml.org/doc/40988},
volume = {97},
year = {2003},
}

TY - JOUR
AU - Ruggeri, Fabrizio
AU - Martín, Jacinto
AU - Ríos Insua, David
TI - Optimal alternative robustness in Bayesian Decision Theory.
JO - RACSAM
PY - 2003
VL - 97
IS - 3
SP - 407
EP - 412
AB - In Martin et al (2003), we suggested an approach to general robustness studies in Bayesian Decision Theory and Inference, based on ε-contamination neighborhoods. In this note, we generalise the results considering neighborhoods based on norms, specifically, the supremum norm for utilities and the total variation norm for probability distributions. We provide tools to detect changes in preferences between alternatives under perturbations of the prior and/or the utility and the most sensitive direction.
LA - eng
KW - Decisión bayesiana; Robustez; sensitivity analysis; class of utilities; class of priors; dominance
UR - http://eudml.org/doc/40988
ER -

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