END随机变量阵列加权和完全收敛性  

Weighted sums and complete convergence of arrays of END random variables

作　　者：张玉 ZHANG Yu(School of Mathematics and Statistics,Chaohu University,Hefei Anhui 238024,China)

机构地区：[1]巢湖学院数学与统计学院,安徽合肥238024

出　　处：《阜阳师范学院学报（自然科学版）》2019年第1期6-9,共4页Journal of Fuyang Normal University(Natural Science)

基　　金：巢湖学院校级科研项目(XLY-201803)资助

摘　　要：随机变量加权在实际应用中十分广泛,研究随机变量加权和的收敛性也有着实际的意义。完全收敛性在收敛性质中属于较强的收敛性质,比a.s收敛的收敛性还要强,所以研究加权和的完全收敛性在概率论极限理论中也有一定意义。本文采取对END随机变量进行截尾,利用Rosenthal型最大值不等式得出END随机变量阵列在较弱条件下的完全收敛性。The weighting of random variables is widely used in practice, and it is of practical significance to study the convergence of weighted sums of random variables. Complete convergence belongs to strong convergence property in convergence property, which is stronger than a.s. convergence and convergence. Therefore, it is of significance to study the complete convergence of weighted sums in probability limit theory. In this paper, the END random variables was truncated and obtained the complete convergence of the END random variable arrays under weaker conditions by using Rosenthal type maximum inequality.

关 键 词：加权 完全收敛 Rosenthal型不等式 截尾 

分 类 号：O211.4[理学—概率论与数理统计]