基于客户来到的二维风险模型的精细大偏差

数学物理学报 ›› 2020, Vol. 40 ›› Issue (4): 1108-1120.

• 论文 • 上一篇

基于客户来到的二维风险模型的精细大偏差

肖鸿民(),王占魁*()

^{西北师范大学数学与统计学院兰州 730070}

收稿日期:2019-06-14 出版日期:2020-08-26 发布日期:2020-08-20
通讯作者: 王占魁 E-mail:xiaohm9@126.com;1185207932@qq.com
作者简介:肖鸿民, E-mail:xiaohm9@126.com
基金资助:
国家自然科学基金(71261023)

The Precise Large Deviations of a Bidimensional Risk Model Based on Customer Arrival

Hongmin Xiao(),Zhankui Wang*()

^{College of Mathematics and Statistics, Northwest Normal University, Lanzhou 730070}

Received:2019-06-14 Online:2020-08-26 Published:2020-08-20
Contact: Zhankui Wang E-mail:xiaohm9@126.com;1185207932@qq.com
Supported by:
the NSFC(71261023)

摘要/Abstract

摘要：

该文讨论基于客户来到的二维风险模型.假设潜在索赔额$\overrightarrow{X^{i}}=（X_{1}^{i}，X_{2}^{i}）^{\top}$是独立同分布的随机向量序列，$X_{1}^{i}$与$X_{2}^{i}$是相依的，在重尾分布族$C$下得到了损失过程部分和与随机和的精细大偏差.

关键词: 保险风险模型, 精细大偏差, 二维, C族, Copula函数

Abstract:

In this paper, we discuss the two-dimensional risk model based on the entrance process. Assuming that $\overrightarrow{X^{i}}=(X_{1}^{i}, X_{2}^{i})^{\top}$ is a two-dimensional random vector sequence with the same distribution, $X_{1}^{i}$ and $X_{2}^{i}$ are dependent, and the precise large deviation between the partial sum and the random sum of loss precess is obtained under the heavy tail distribution family C.

Key words: Insurance risk model, Precise large deviations, Two-dimensional, C class, Copula funtions

中图分类号:

O211.4

肖鸿民,王占魁. 基于客户来到的二维风险模型的精细大偏差[J]. 数学物理学报, 2020, 40(4): 1108-1120.

Hongmin Xiao,Zhankui Wang. The Precise Large Deviations of a Bidimensional Risk Model Based on Customer Arrival[J]. Acta mathematica scientia,Series A, 2020, 40(4): 1108-1120.

参考文献 12

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基于客户来到的二维风险模型的精细大偏差

The Precise Large Deviations of a Bidimensional Risk Model Based on Customer Arrival

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