arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2001.03320math.PR
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三状态马氏相依随机变量和的渐近性

Asymptotics for the sum of three state Markov dependent random variables

Gabija Liaudanskaitė, Vydas Čekanavičius

摘要:

研究了当索赔额依赖于被保险人的状态(健康、生病或死亡)且索赔连接在一个马尔可夫链中时的保险模型。在$n\in \mathbb {N}$周期后,将带符号复合泊松近似应用于总索赔分布。对于局部范数和一致范数,分别得到了阶$O(n^{-1})$和$O(n^{-1/2})$的精度.在一个特定的情况下,在全变差和非均匀估计的估计的准确性被证明是至少为顺序$O(n^{-1})$。采用了特征函数法。研究结果可用于估计保险人可能遭受的损失,从而优化保险费。

英文摘要:

The insurance model when the amount of claims depends on the state of the insured person (healthy, ill, or dead) and claims are connected in a Markov chain is investigated. The signed compound Poisson approximation is applied to the aggregate claims distribution after $n\in \mathbb {N}$ periods. The accuracy of order $O(n^{-1})$ and $O(n^{-1/2})$ is obtained for the local and uniform norms, respectively. In a particular case, the accuracy of estimates in total variation and non-uniform estimates are shown to be at least of order $O(n^{-1})$. The characteristic function method is used. The results can be applied to estimate the probable loss of an insurer to optimize an insurance premium.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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