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车辆保险产品的定价一般会考虑保单持有人的索赔概率和期望索赔额等两个因素,零调整逆高斯回归模型作为解决这类问题的一个有力工具,由于变量分布的限定,从而具有一定的局限性.针对该问题,本文基于零调整逆高斯回归模型和分位数回归模型的思想,提出零调整分位数回归模型,并结合实际数据进行了拟合分析.与零调整逆高斯回归模型拟合的结果比较表明,零调整分位数回归模型可以作为研究车辆保险中索赔额的一个有力工具.
The pricing of vehicle insurance products usually takes into account the policyholder’s claim probability and the expected amount of compensation. Zero-adjusted inverse Gaussian regression model is a powerful tool to solve such problems. Due to the limited distribution of variables, it has a certain This paper presents a regression model of zero adjustment quantile based on the idea of zero adjustment inverse Gaussian regression model and quantile regression model, and combined with the actual data fitting.Compared with zero adjustment inverse Gaussian regression model The fitting results show that the zero-adjusted quantile regression model can be used as a powerful tool to study the claim amount in the vehicle insurance.