论文标题
一个基于副本的双变量复合模型家族，用于要求严重性建模
A Copula-Based family of Bivariate Composite Models for Claim Severity Modelling
论文作者
论文摘要
在本文中，我们考虑以灵活的方式对共同类型的索赔及其相关成本进行建模的双变量复合模型。出于说明性目的，Gumbel Copula与复合的Weibull Inverse Weibull，Paralogistic Inverse Weibull和Burr Inverse Weibull边缘模型配对。由欧洲汽车保险公司的汽车保险人体伤害和财产损坏数据安装了最终的双变量复合模型，其参数是通过利润方法的推理功能估算的。
In this paper, we consider bivariate composite models for modeling jointly different types of claims and their associated costs in a flexible manner. For expository purposes, the Gumbel copula is paired with the composite Weibull-Inverse Weibull, Paralogistic-Inverse Weibull, and Inverse Burr-Inverse Weibull marginal models. The resulting bivariate copula-based composite models are fitted on motor insurance bodily injury and property damage data from a European motor insurance company and their parameters are estimated via the inference functions for margins method.
