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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A Bayesian Decision-Theoretic Approach to Logically-Consistent Hypothesis Testing

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Author(s):
da Silva, Gustavo Miranda [1] ; Esteves, Luis Gustavo [1] ; Fossaluza, Victor [1] ; Izbicki, Rafael [2] ; Wechsler, Sergio [1]
Total Authors: 5
Affiliation:
[1] Univ Sao Paulo, Inst Math & Stat, BR-05508090 Sao Paulo - Brazil
[2] Univ Fed Sao Carlos, Dept Stat, BR-13565905 Sao Carlos, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: Entropy; v. 17, n. 10, p. 6534-6559, OCT 2015.
Web of Science Citations: 4
Abstract

This work addresses an important issue regarding the performance of simultaneous test procedures: the construction of multiple tests that at the same time are optimal from a statistical perspective and that also yield logically-consistent results that are easy to communicate to practitioners of statistical methods. For instance, if hypothesis A implies hypothesis B, is it possible to create optimal testing procedures that reject A whenever they reject B? Unfortunately, several standard testing procedures fail in having such logical consistency. Although this has been deeply investigated under a frequentist perspective, the literature lacks analyses under a Bayesian paradigm. In this work, we contribute to the discussion by investigating three rational relationships under a Bayesian decision-theoretic standpoint: coherence, invertibility and union consonance. We characterize and illustrate through simple examples optimal Bayes tests that fulfill each of these requisites separately. We also explore how far one can go by putting these requirements together. We show that although fairly intuitive tests satisfy both coherence and invertibility, no Bayesian testing scheme meets the desiderata as a whole, strengthening the understanding that logical consistency cannot be combined with statistical optimality in general. Finally, we associate Bayesian hypothesis testing with Bayes point estimation procedures. We prove the performance of logically-consistent hypothesis testing by means of a Bayes point estimator to be optimal only under very restrictive conditions. (AU)

FAPESP's process: 14/25302-2 - A flexible approach to high-dimensional conditional density estimation
Grantee:Rafael Izbicki
Support Opportunities: Regular Research Grants
FAPESP's process: 09/03385-5 - Classes of hypotheses tests
Grantee:Rafael Izbicki
Support Opportunities: Scholarships in Brazil - Master