On a New Class of Multivariate Prior Distributions: Theory and Application in Reliability

Identificadores
URI: http://hdl.handle.net/10498/24507
DOI: 10.1214/19-BA1191
ISSN: 1931-6690
ISSN: 1936-0975 (internet)
Files
Statistics
Metrics and citations
Share
Metadata
Show full item recordDate
2021-03Department
Estadística e Investigación OperativaSource
Bayesian Analysis (2021) 16, Number 1, pp. 31–60Abstract
n 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.
Subjects
robust Bayesian analysis; Bayesian sensitivity; class of priors; stochastic orders; multivariate total positivity; weighted distributionsCollections
- Artículos Científicos [4821]
- Articulos Científicos Est. I.O. [123]
- Artículos Científicos INDESS [384]