A new efficient method for estimating the Gerber–Shiu function in the classical risk model
A new efficient method for estimating the Gerber–Shiu function in the classical risk model
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DOI：
10.1080/03461238.2017.1371068
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发表时间：
2018-05
影响因子：
1.8
通讯作者：
Zhimin Zhang;Wen Su
中科院分区：
文献类型：
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作者：
Zhimin Zhang;Wen Su
摘要本文提出了一种新的估计经典风险模型中Gerber-Shiu折现罚函数的有效方法。我们开发的Gerber-Shiu函数的Laguerre的基础上，然后估计的未知系数的样本信息的基础上索赔数量和个人索赔规模。给出了估计的收敛速度。仿真结果表明，当样本容量有限时，该估计具有很好的性能。我们还表明，所提出的估计优于其他估计在模拟研究。
Abstract In this paper, we propose a new efficient method for estimating the Gerber–Shiu discounted penalty function in the classical risk model. We develop the Gerber–Shiu function on the Laguerre basis, and then estimate the unknown coefficients based on sample information on claim numbers and individual claim sizes. The convergence rate of the estimate is derived. Some simulation examples are illustrated to show that the estimate performs very well when the sample size is finite. We also show that the proposed estimate outperforms other estimates in the simulation studies.