A multivariate Poisson regression model for count data

被引：4
|
作者：
Munoz-Pichardo, J. M. [1 ]
Pino-Mejias, R. [1 ]
Garcia-Heras, J. [1 ]
Ruiz-Munoz, F. [2 ]
Luz Gonzalez-Regalado, M. [2 ]
机构：
[1] Univ Seville, Dept Estadist & IO, Avd Reina Mercedes S-N, Seville 41012, Spain
[2] Univ Huelva, Dept Geodinam & Paleontol, Huelva, Spain
来源：
JOURNAL OF APPLIED STATISTICS | 2021年 / 48卷 / 13-15期
关键词：
Poisson log-linear model; maximum likelihood estimation; selection model; multivariate count data; conditional modeling;
D O I：
10.1080/02664763.2021.1877637
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：
We propose a new technique for the study of multivariate count data. The proposed model is applied to the study of the number of individuals several fossil species found in a set of geographical observation points. First, we are proposing a multivariate model based on the Poisson distributions, which allows positive and negative correlations between the components. We are extending the log-linear Poisson model in the multivariate case through the conditional distributions. For this model, we obtain the maximum likelihood estimates and compute several goodness of fit statistics. Finally we illustrate the application of the proposed method over data sets: various simulated data sets and a count data set of various fossil species.
引用
收藏
页码：2525 / 2541
页数：17
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