A symptotic Behavior of Convolution of Dependent Random Variables with Heavy-Tailed Distributions

被引:0
|
作者
Ranjbar, V. Y. [1 ]
Amini, M. [1 ]
Bozorgnia, A. [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 / 02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 X-1 and X-2 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.
引用
收藏
页码:217 / 230
页数:14
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