Abstract:
|
To model correlated bivariate count data with extra zero observations, this paper proposes two new bivariate zero-inflated generalized Poisson (ZIGP) distributions by incorporating a multiplicative factor (or dependency parameter) ?, named as Type I and Type II bivariate ZIGP(?) distributions, respectively. The proposed distributions possess a flexible correlation structure and can be used to fit either positively or negatively correlated and either over- or under-dispersed count data, comparing to the existing models that can only fit positively correlated count data with over-dispersion. The two marginal distributions share a common parameter of zero inflation in Type I bivariate ZIGP(?) while have their own parameters of zero inflation in Type II bivariate ZIGP(?), resulting in a much wider range of applications. The important distributional properties are explored and some useful statistical inference methods including MLE of parameters, bootstrap confidence intervals and related testing hypotheses are developed. A real data are thoroughly analyzed by using the proposed distributions. Several simulation studies are conducted to evaluate the performance of the proposed methods.
|
ASA Meetings Department
732 North Washington Street, Alexandria, VA 22314
(703) 684-1221 • meetings@amstat.org
Copyright © American Statistical Association.