Asymptotic Behavior of Convolution of Dependent Random Variables with Heavy-Tailed Distributions

被引：0
|
作者：
Ranjbar, Vahid Y. [1 ]
Amini, Mohammad [1 ]
Bozorgnia, Abolghasem [1 ]
机构：
[1] Ferdowsi Univ Mashhad, Fac Math Sci, Ordered & Spatial Data Ctr Excellence, Dept Stat, Mashhad 917551159, Iran
来源：
THAI JOURNAL OF MATHEMATICS | 2009年 / 7卷 / 01期
关键词：
Weakly Negative Dependence (WND); Negative Quadratic Dependent (NQD); Heavy-Tailed; Long-Tailed; Asymptotic behavior;
D O I：
暂无
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
In this paper, we study the asymptotic behavior of the tail of X-1 + X-2 in a dependent framework; where Xi and X2 are two positive heavy-tailed random variables with continuous joint and common marginal distribution functions F(x, y) and F(x), respectively; and for some classes of heavy-tailed distributions, we obtain some bounds and convolution properties. Furthermore, we prove P(vertical bar X-1 - X-2 vertical bar > x) similar to a.P(vertical bar X vertical bar > x) as x -> infinity, where a is a constant and X-1, X-2 are dependent random variables.
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页码：21 / 34
页数：14
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