论文标题
具有不同阈值及其保险申请的复合日志正态回归模型
Composite Lognormal-T regression models with varying threshold and its insurance application
论文作者
论文摘要
综合概率模型显示出非常有希望的结果，用于建模由小，中和大损失组成的声明严重性数据。在本文中，我们介绍了具有不同阈值的三类参数复合回归模型。我们考虑了复合家族的尾部部分的头部和毛刺，stoppa和burr的对数正态分布。此外，模式匹配过程已用于两种密度的组成。为了捕获保单持有人特征的异质行为，将协变量引入到尾部分布的比例参数中。最后，已使用现实世界中的保险数据集显示了拟议模型的适用性。
Composite probability models have shown very promising results for modeling claim severity data comprised of small, moderate, and large losses. In this paper, we introduce three classes of parametric composite regression models with a varying threshold. We consider the Lognormal distribution for the head and the Burr, the Stoppa and the generalized log-Moyal (GlogM) distributions for the tail part of the composite family. Further, the Mode-Matching procedure has been utilized for the composition of the two densities. To capture the heterogeneous behavior of the policyholder's characteristics, covariates are introduced into the scale parameter of the tail distribution. Finally, the applicability of the proposed models has been shown using a real-world insurance data set.
