A latent class poisson regression model for heterogeneous count data
提出一种处理计数数据中异质性的泊松回归模型，假设截距和解释变量系数均来自离散混合分布，形成有限混合模型，并用EM算法估计，应用于图书直邮客户购买数据。
Abstract In this paper an approach is developed that accommodates heterogeneity in Poisson regression models for count data. The model developed assumes that heterogeneity arises from a distribution of both the intercept and the coefficients of the explanatory variables. We assume that the mixing distribution is discrete, resulting in a finite mixture model formulation. An EM algorithm for estimation is described, and the algorithm is applied to data on customer purchases of books offered through direct mail. Our model is compared empirically to a number of other approaches that deal with heterogeneity in Poisson regression models.