随机变量的负超可加相依及其应用(英文)  

Negatively Superadditive Dependence of Random Variables with Applications

作　　者：胡太忠[1] 

机构地区：[1]中国科学技术大学统计与金融系,合肥230026

出　　处：《应用概率统计》2000年第2期133-144,共12页Chinese Journal of Applied Probability and Statistics

基　　金：NSFC Grant 19701030 and a grant of Chinese Academy of Sciences.

摘　　要：一个随机向量Ｘ＝（Ｘ１，Ｘ２，…，Ｘｍ）称为负超可加相依（ＮＳＤ），如果对每个超可加函数，Ｅ（Ｘ１Ｘ２....，Ｘｍ）≤Ｅ（Ｙ１，Ｙ２，…，Ｘｍ）其中Ｙ１，Ｙ２，...，Ｙｍ相互独立且对任意ｉ，Ｙｉ＝Ｘｉ本文研究了ＮＳＤ的基本性质，给出了ＮＳＤ判定的三个结构性定理，并且这些定理可用来证明许多著名的多元分布具有ＮＳＤ性质．本文还给出了ＮＳＤ的许多概率不等式．A random vector X = (X1, X2,... , Xm) is said to be negatively superadditive dependent (NSD) if for every superadditive function , E(X1, X2,..., Xm)≤5 E(Y1, Y2,..,Ym) where Y1, Y2,..., Ym are independent with Yi=Xi for each i. Some basic properties and three structural theorems of NSD are derived and applied to show that a number of well-known multivariate distributions possess the NSD property. Applications are also presented.

关 键 词：负相依 负相协 负超可加相依 NSD 随机变量 

分 类 号：O212.5[理学—概率论与数理统计]