非负不同分布负相伴随机变量下的精细大偏差

Precise Large Deviations of Nonnegative, Non-identical and Negatively Associated Random Variables

研究非负,不同分布,负相伴随机变量的精细大偏差问题.在相对较弱的条件下,重点解决非随机和的精细大偏差的下限问题,得到相对应的随机和的一致渐近结论.同时,对复合更新风险模型进行深入的讨论,在一定的条件之下将其简化为一般的更新风险模型,并将所得相关的精细大偏差的结论应用到更为实际的复合更新风险模型中,验证其理论与实际价值.除此之外,本文的研究还表明,随机变量间的这种相依关系对精细大偏差的最终结果的影响并不大.

In this paper, precise large deviations of nonnegative, non-identical distributions and negatively associated random variables are investigated. Under certain conditions, the lower bound of the precise large deviations for the non-random sums is solved and the uniformly asymptotic results for the corresponding random sums are obtained. At the same time, we deeply discussed the compound renewal risk model, in which we found that the compound renewal risk model can be equivalent to renewal risk model under certain conditions. The relative research results of precise large deviations are applied to the more practical compound renewal risk model, and the theoretical and practical values are verified. In addition, this paper also shows that the impact of this dependency relationship between random variables to precise large deviations of the final result is not significant.