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Specification of Informative Prior Distributions for Multinomial Models Using Vine Copulas

Lookup NU author(s): Professor Kevin Wilson

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This is the final published version of an article that has been published in its final definitive form by International Society for Bayesian Analysis, 2018.

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Abstract

We consider the specification of an informative prior distribution for the probabilities in a multinomial model. We utilise vine copulas: flexible multivariate distributions built using bivariate copulas stacked in a tree structure. We take advantage of a specific vine structure, called a D-vine, to separate the specification of the multivariate prior distribution into that of marginal distributions for the probabilities and parameter values for the bivariate copulas in the vine. We provide guidance on each of the choices to be made in the prior specification and each of the questions to ask the expert to specify the model parameters within the context of an engineering application. We then give full details of the approach for the general problem.

Publication metadata

Author(s): Wilson KJ

Publication type: Article

Publication status: Published

Journal: Bayesian Analysis

Year: 2018

Volume: 13

Issue: 3

Pages: 749-766

Online publication date: 09/10/2017

Acceptance date: 15/08/2017

Date deposited: 10/10/2017

ISSN (print): 1936-0975

ISSN (electronic): 1931-6690

Publisher: International Society for Bayesian Analysis

URL: https://doi.org/10.1214/17-BA1068

DOI: 10.1214/17-BA1068

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