Bivariate Conway-Maxwell-Poisson distribution: Formulation, properties, and inference

JOURNAL OF MULTIVARIATE ANALYSIS

卷:150

Article

Sellers, Kimberly F.^1,2  Morris, Darcy Steeg²  Balakrishnan, Narayanaswamy³ 

[1] Georgetown Univ, Dept Math & Stat, Washington, DC 20057 USA

[2] US Bur Census, Ctr Stat Res & Methodol, Washington, DC 20233 USA

[3] McMaster Univ, Dept Math & Stat, Hamilton, ON L8S 4K1, Canada

关键词: Bivariate distribution;    Dispersion;    Dependence;    Conway-Maxwell-Poisson (COM-Poisson);   

DOI  :  10.1016/j.jmva.2016.04.007

来源: Elsevier

【 摘 要 】

The bivariate Poisson distribution is a popular distribution for modeling bivariate count data. Its basic assumptions and marginal equi-dispersion, however, may prove limiting in some contexts. To allow for data dispersion, we develop here a bivariate Conway-Maxwell-Poisson (COM-Poisson) distribution that includes the bivariate Poisson, bivariate Bernoulli, and bivariate geometric distributions all as special cases. As a result, the bivariate COM-Poisson distribution serves as a flexible alternative and unifying framework for modeling bivariate count data, especially in the presence of data dispersion. Published by Elsevier Inc.

【 授权许可】

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