Bayesian analyses of an exponential-Poisson and related zero augmented type models

© 2020 Informa UK Limited, trading as Taylor & Francis Group.

Détails bibliographiques
Publié dans:Journal of applied statistics. - 1991. - 49(2022), 4 vom: 17., Seite 949-967
Auteur principal: Scollnik, David P M (Auteur)
Format: Article en ligne
Langue:English
Publié: 2022
Accès à la collection:Journal of applied statistics
Sujets:Journal Article 62f15 62p12 Bayesian Markov chain Monte Carlo exponential-Poisson hurdle zero-inflated
Description
Résumé:© 2020 Informa UK Limited, trading as Taylor & Francis Group.
We consider several alternatives to the continuous exponential-Poisson distribution in order to accommodate the occurrence of zeros. Three of these are modifications of the exponential-Poisson model. One of these remains a fully continuous model. The other models we consider are all semi-continuous models, each with a discrete point mass at zero and a continuous density on the positive values. All of the models are applied to two environmental data sets concerning precipitation, and their Bayesian analyses using MCMC are discussed. This discussion covers convergence of the MCMC simulations and model selection procedures and considerations
Description:Date Revised 16.06.2022
published: Electronic-eCollection
Citation Status PubMed-not-MEDLINE
ISSN:0266-4763
DOI:10.1080/02664763.2020.1846692