Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1145159 | Journal of Multivariate Analysis | 2016 | 17 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Numerical Analysis
Authors
Kimberly F. Sellers, Darcy Steeg Morris, Narayanaswamy Balakrishnan,