离散半马氏风险模型中的期望罚金函数（英文）  

On the Expected Penalty Functions in a Discrete Semi-Markov Risk Model

作　　者：刘海燕[1] 陈密[1] 

机构地区：[1]福建师范大学数学与计算机科学学院,福州350117

出　　处：《应用概率统计》2016年第6期592-602,共11页Chinese Journal of Applied Probability and Statistics

基　　金：supported by the National Natural Science Foundation of China(11426063);the Natural Science Foundation of Fujian Province(2015J05003);the Scientific Research Foundation of Fujian Provincial Education Department(JA14077)

摘　　要：本文研究离散半马氏风险模型中的期望罚金函数,所考虑的模型包含了多个已有的风险模型,如(具有延迟索赔)复合二项模型和(具有延迟索赔)复合马氏二项模型.通过一个简单的方法得到了两状态模型中期望罚金函数的递推公式和初始值.我们也对所得结果给出了一些应用.This paper considers the expected penalty functions for a discrete semi-Markovrisk model, which includes several existing risk models such as the compound binomial model （with time-correlated claims） and the compound Markov binomial model （with time-correlated claims） as special cases. Recursive formulae and the initial values for the discounted free penalty functions are derived in the two-state model by an easy method. We also give some applications of our results.

关 键 词：期望罚金函数 母函数 递推公式 半马氏风险模型 

分 类 号：O211.6[理学—概率论与数理统计]