Flexible (panel) Regression Models for Bivariate Count–Continuous Data with an Insurance Application
提出一种灵活回归模型，处理混合计数-连续面板数据，基于复合泊松表示和多项式展开的二元随机效应，具有封闭形式预测更新公式，适用于保险保费根据历史索赔动态调整的场景。
Summary We propose a flexible regression model that is suitable for mixed count–continuous panel data. The model is based on a compound Poisson representation of the continuous variable, with bivariate random effect following a polynomial-expansion-based joint density. Besides the distributional flexibility that it offers, the model allows for closed form forecast updating formulae. This property is especially important for insurance applications, in which the future individual insurance premium should be regularly updated according to one’s own past claim history. An application to vehicle insurance claims is provided.