A Multivariate Generalized Poisson Regression Model

被引：17
|
作者：
Famoye, Felix [1 ]
机构：
[1] Cent Michigan Univ, Dept Math, Mt Pleasant, MI 48859 USA
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2015年 / 44卷 / 03期
关键词：
Correlated data; Count data; Estimation; Over-and under-dispersion; Test; NEGATIVE BINOMIAL REGRESSION; COUNT DATA; HEALTH-CARE; DISTRIBUTIONS; COPULAS; DEMAND; FAMILY;
D O I：
10.1080/03610926.2012.743565
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：
A multivariate generalized Poisson regression model based on the multivariate generalized Poisson distribution is defined and studied. The regression model can be used to describe a count data with any type of dispersion. The model allows for both positive and negative correlation between any pair of the response variables. The parameters of the regression model are estimated by using the maximum likelihood method. Some test statistics are discussed, and two numerical data sets are used to illustrate the applications of the multivariate count data regression model.
引用
收藏
页码：497 / 511
页数：15
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