유한 혼합 이변량 포아송 회귀모형에 대한 베이지안 추론: 호주 의료 서비스 자료에의 적용

초록

Excess zero data are observed in various research fields such as social science, natural science, medicine, and engineering. In these data, if two response variables are correlated, we can consider a bivariate Poisson model and random effects may be included to take into account the heterogeneity of unobserved data. Furthermore, a finite mixture of bivariate Poisson models can be applied to explain the overdispersion of zero inflated data. We propose a Bayesian infernece for the finite mixture of bivariate Poisson models with random effects when there is a correlation between the two response variables. In order to determine a model with the optimal number of components, the deviance information criterion was computed in the models. We applied the proposed model to the Australian health survey data, and checked the performance of the model.

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