Bivariate doubly inflated Poisson models with applications

Bayesian Analysis of Doubly Inflated Poisson Regression for Correlated Count Data: Application to DMFT Data

“…[4]. Sengupta et al (2015) developed two bivariate DIP models to develop paired count data with inflated frequencies. They demonstrated that maximum likelihood estimators were relatively more efficient than [7].…”

“…As a result, a Metropolis-Hastings (M-H) algorithm in the MCMC method is utilized to generate samples within Gibbs iterations [14,16,17]. For the ZIP regression model, we obtained the full conditional posterior distributions for the parameters based on Equation [5] (See Appendix A).…”

“…Bivariate DIP models were proposed by Pooja Sengupta et al (2015). In this article, authors introduced a bivariate distribution for count data with the inflated count in both (0,0) and (k,k) cells for k>0.…”

“…Bivariate responses included the joint count of , the number of physician visits, and , the number of medications prescribed for the patient. Cell frequencies were larger in (0,0) and (1,1) than all other cells [5]. Sumen sen et al (2018) used Gaussian copula for modeling multivariate doubly inflated Poisson.…”

“…In the DIP study by Chandra (2011), parameters' estimates have been examined through maximum likelihood and the method of moments techniques. Moreover, in a study conducted by Sengupta et al (2015)., parameters' estimate has been obtained using the maximum likelihood method [4,5].…”