The necessary and sufficient conditions for a probability distribution belongs to the domain of geometric attraction of standard Laplace distribution

T. Hung, P. Kien
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引用次数: 1

Abstract

The geometric sums have been arisen from the necessity to resolve practical problems in ruin prob- ability, risk processes, queueing theory and reliability models, etc. Up to the present, the results related to geometric sums like asymptotic distributions and rates of convergence have been investigated by many mathematicians. However, in a lot of various situations, the results concerned domains of geometric attraction are still limitative. The main purpose of this article is to introduce concepts on the domain of geometric attraction of standard Laplace distribution. Using method of characteristic functions, the necessary and sufficient conditions for a probability distribution belongs to the domain of geometric attraction of standard Laplace distribution are shown. In special case, obtained result is a weak limit theorem for geometric sums of independent and identically distributed random variables which has been well-known as the second central limit theorem. Furthermore, based on the obtained results of this paper, the analogous results for the domains of geometric attraction of exponential distribution and Linnik distribution can be established. More generally, we may extend results to the domain of geometric attraction of geometrically strictly stable distributions.      
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一个概率分布的充要条件属于标准拉普拉斯分布的几何吸引域
几何和是解决破产概率、风险过程、排队论和可靠性模型等实际问题的需要而产生的。迄今为止,许多数学家已经研究了关于几何和的渐近分布和收敛率等问题。然而,在许多不同的情况下,有关几何引力领域的结果仍然是有限的。本文的主要目的是介绍标准拉普拉斯分布的几何吸引域的概念。利用特征函数的方法,给出了一个概率分布属于标准拉普拉斯分布的几何吸引域的充要条件。在特殊情况下,得到的结果是独立同分布随机变量几何和的弱极限定理,即众所周知的第二中心极限定理。在此基础上,可以得到指数分布和林尼克分布的几何吸引域的类似结果。更一般地说,我们可以将结果推广到几何严格稳定分布的几何吸引域。
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