The zero-inflated Conway-Maxwell-Poisson distribution: Bayesian inference, regression modeling and influence diagnostic
Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
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Data(s) |
18/03/2015
18/03/2015
01/11/2014
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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 |