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

被引：32

作者：

Barriga, Gladys D. C. ^{[1
]}

Louzada, Francisco ^{[2
]}

机构：

[1] Sao Paulo State Univ, Fac Engn Bauru, Sao Paulo, Brazil

[2] Univ Sao Paulo, Dept Appl Maths & Stat, BR-05508 Sao Paulo, Brazil

来源：

STATISTICAL METHODOLOGY | 2014年 / 21卷

关键词：

Bayesian inference; COM-Poisson distribution; Kullback-Leibler distance; Zero-inflated models; BINOMIAL REGRESSION; DIVERGENCE MEASURES; COUNT DATA;

D O I：

10.1016/j.stamet.2013.11.003

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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.

引用

页码：23 / 34

页数：12

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