Multivariate Gamma-Poisson Models
多元伽马—泊松模型
This article extends the multivariate gamma-Poisson model of repeated events, developed by Arbous and Kerrich (1951) and Bates and Neyman (1952), by (a) compounding it with a Dirichlet distribution in the analysis of cross-sectional data and by (b) allowing individual rates to shift at the start of the second period in the analysis of two-period longitudinal data. The first extension allows individuals to specialize in particular types of events. The model is shown to…