重尾相依随机变量的随机加权和尾概率的渐近估计（英文）  

Approximation of the Tail Probabilities of Randomly Weighted Sums in Presence of Dependence and Heavy Tails

作　　者：唐风琴[1] 白建明[2] 

机构地区：[1]淮北师范大学数学科学学院,淮北235000 [2]兰州大学管理学院,兰州730000

出　　处：《应用概率统计》2016年第2期111-120,共10页Chinese Journal of Applied Probability and Statistics

基　　金：supported by the National Nature Science Foundation of China(71171103);the General Natural Science Foundation of the Anhui Higher Education Institutions of China(KJ2014B15)

摘　　要：令{X_k;k≥1}为一列实值随机变量,{θ_k;k≥1}为另一列与之独立的随机变量序列.假设{X_k;k≥1}为两两广义负象限相依且服从重尾分布,在{θ_k;k≥1}独立和相依条件下,本文得到了一些渐近估计.Let {Xk;k ≥ 1} be a sequence of real-valued random variables and {θk;k ≥ 1} be other n random variables which are independent of the form sequence.Suppose that {Xk;k≥ 1}are pairwise generalized negatively orthant dependent with heavy tails under the condition that{θk;k ≥ 1} are independent or associated,some asymptotic formulas are established.

关 键 词：随机加权和 两两广义负象限相依 重尾分布 正相依 

分 类 号：O211.2[理学—概率论与数理统计]