Skip to Main Content (Press Enter)

Logo CNR
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills

UNI-FIND
Logo CNR

|

UNI-FIND

cnr.it
  • ×
  • Home
  • People
  • Outputs
  • Organizations
  • Expertise & Skills
  1. Outputs

On a new class of multivariate prior distributions: Theory and application in reliability

Academic Article
Publication Date:
2021
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.
Iris type:
01.01 Articolo in rivista
Keywords:
robust Bayesian analysis; Bayesian sensitivity; class of priors; stochastic orders; multivariate total positivity; weighted distributions
List of contributors:
Ruggeri, Fabrizio
Handle:
https://iris.cnr.it/handle/20.500.14243/404428
Published in:
BAYESIAN ANALYSIS
Journal
  • Overview

Overview

URL

https://projecteuclid.org/journals/bayesian-analysis/volume-16/issue-1/On-a-New-Class-of-Multivariate-Prior-Distributions--Theory/10.1214/19-BA1191.full
  • Use of cookies

Powered by VIVO | Designed by Cineca | 26.5.0.0 | Sorgente dati: PREPROD (Ribaltamento disabilitato)