检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:许蕊 卢志义[1] XU-Rui;LU Zhi-yi(School of Science,Tianjin University of Commerce,Tianjin 300134,China)
出 处:《数学的实践与认识》2023年第2期118-127,共10页Mathematics in Practice and Theory
基 金:国家自然科学基金面上项目“基于机器学习的长期护理保险精算预测模型与风险分析”(71771163)。
摘 要:对基于Hoerl曲线的非寿险未决赔款准备金估计模型的不足进行了讨论,并对其进行了改进.将改进的Hoerl曲线做为预测量而建立的指数族非线性模型具有更大的灵活性,因而更适用于未决赔款准备金的估计.通过模拟实验对改进的Hoerl曲线在未决赔款准备金估计中的应用进行了验证,并与经典泊松链梯模型以及基于Hoerl曲线的模型进行了对比分析.结论表明,对于先缓慢增长至顶点,然后快速回落的赔付模式,改进的Hoerl曲线具有更好的预测效果.The drawbacks of the stochastic models for claims reserving based on Hoerl curve are discussed and are improved accordingly.The non-linear models of exponential family based on improved Hoerl curve offer more flexibility and is more proper to claims reserving.The effectiveness of the model based on the improved Hoerl curve is illustacted through a simulation examples and the model is compared to the classical Poisson chain ladder model and the model based on Hoerl curve.It is shown that the model based on the improved Hoerl curve has better predicting results than other models for the shape of the run-off of incremental claims that is increase slowly to a peak,then dying off rapidly.
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.38