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Felix Famoye

Central Michigan University



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61 – Modeling Multivariate Count Data: Multivariate Extensions and Generalizations of Standard Count Distributions

Bivariate Exponentiated-Exponential Geometric Regression Model

Sponsor: Government Statistics Section
Keywords: Correlated count data, dispersion, estimation, goodness-of-fit

Felix Famoye

Central Michigan University

A bivariate exponentiated-exponential geometric regression (BEEGR) model that allows any type of correlation is defined and studied. The regression model is based on the univariate exponentiated-exponential geometric distribution and the marginal means of the bivariate model are functions of the explanatory variables. The parameters of the bivariate regression model are estimated by using the maximum likelihood method. Some test statistics including goodness-of-fit are discussed. One numerical data set is used to illustrate the applications of the regression model.

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