The zero-inflated Conway-Maxwell-Poisson distribution: Bayesian inference, regression modeling and influence diagnostic


Autoria(s): Barriga, Gladys Dorotea Cacsire; Louzada, Francisco
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

18/03/2015

18/03/2015

01/11/2014

Resumo

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

In this paper we propose the zero-inflated COM-Poisson distribution. We develop a Bayesian analysis for our model via on Markov chain Monte Carlo methods. We discuss regression modeling and model selection, as well as, develop case deletion influence diagnostics for the joint posterior distribution based on the psi-divergence, which has several divergence measures as particular cases, such as the Kullback-Leibler (K-L), J-distance, L-1 norm and chi(2)-square divergence measures. The performance of our approach is illustrated in an artificial dataset as well as in a real dataset on an apple cultivar experiment. (C) 2014 Elsevier B.V. All rights reserved.

Formato

23-34

Identificador

http://dx.doi.org/10.1016/j.stamet.2013.11.003

Statistical Methodology. Amsterdam: Elsevier Science Bv, v. 21, p. 23-34, 2014.

1572-3127

http://hdl.handle.net/11449/116751

10.1016/j.stamet.2013.11.003

WOS:000340336800002

Idioma(s)

eng

Publicador

Elsevier B.V.

Relação

Statistical Methodology

Direitos

closedAccess

Palavras-Chave #Bayesian inference #COM-Poisson distribution #Kullback-Leibler distance #Zero-inflated models
Tipo

info:eu-repo/semantics/article