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March 2021 On a New Class of Multivariate Prior Distributions: Theory and Application in Reliability
Fabrizio Ruggeri, Marta Sánchez-Sánchez, Miguel Ángel Sordo, Alfonso Suárez-Llorens
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Bayesian Anal. 16(1): 31-60 (March 2021). DOI: 10.1214/19-BA1191

Abstract

In the context of robust Bayesian analysis for multiparameter distributions, we introduce a new class of priors based on stochastic orders, multivariate total positivity of order 2 (MTP2) and weighted distributions. We provide the new definition, its interpretation and the main properties and we also study the relationship with other classical classes of prior beliefs. We also consider the Hellinger metric and the Kullback-Leibler divergence to measure the uncertainty induced by such a class, as well as its effect on the posterior distribution. Finally, we conclude the paper with a real example about train door reliability.

Acknowledgments

The research was partially supported by Ministerio de Economía y Competitividad (Spain) under grants MTM2017-89577-P.

Citation

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Fabrizio Ruggeri. Marta Sánchez-Sánchez. Miguel Ángel Sordo. Alfonso Suárez-Llorens. "On a New Class of Multivariate Prior Distributions: Theory and Application in Reliability." Bayesian Anal. 16 (1) 31 - 60, March 2021. https://doi.org/10.1214/19-BA1191

Information

Published: March 2021
First available in Project Euclid: 20 December 2019

MathSciNet: MR4194272
Digital Object Identifier: 10.1214/19-BA1191

Subjects:
Primary: 62F15
Secondary: 60E15

JOURNAL ARTICLE
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Vol.16 • No. 1 • March 2021
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