相依随机变量阵列加权和的矩完全收敛性（英文）  

COMPLETE MOMENT CONVERGENCE OF WEIGHTED SUMS FOR ARRAYS OF DEPENDENT RANDOM VARIABLES

作　　者：郭明乐[1] 戴钰[1] 张立君[1] GUO Ming-le DAI Yu ZHANG Li-jun(School of Mathematics and Computer Science, Anhui Normal University, Wuhu 241003, China)

机构地区：[1]安徽师范大学数学计算机科学学院,安徽芜湖241003

出　　处：《数学杂志》2016年第6期1120-1132,共13页Journal of Mathematics

基　　金：Supported by the National Natural Science Foundation of China(11271020;11201004);the Key Project of Chinese Ministry of Education(211077);the Natural Science Foundation for Colleges and Universities in Anhui Province(KJ2014A083);the Anhui Provincial Natural Science Foundation(1508085MA11)

摘　　要：本文研究了相依随机变量阵列加权和的矩完全收敛性.利用矩不等式和截尾法,建立了相依随机变量阵列加权和的矩完全收敛性的充分条件.将Volodin等(2004)及陈平炎等(2006)的关于独立随机变量阵列的结果推广到了负相协和负相依随机变量阵列的情形,推广并完善了Sung(2011),吴群英(2012)及郭明乐和祝东进(2012)的结果.In this paper,the complete moment convergence of weighted sums for sequences of dependent random variables is investigated.By applying moment inequality and truncation methods,some sufficient conditions of complete moment convergence of weighted sums for sequences of dependent random variables are established.We extend the results of Volodin et al.（2004）and Chen et al.（2006） for independent random variables to negatively associated and negatively dependent random variables,which improve and generalize the results of Sung（2011）,Wu（2012）and Guo and Zhu（2012）.

关 键 词：负相协 负相依 ρ＊混合 矩完全收敛性 完全收敛性 

分 类 号：O211.4[理学—概率论与数理统计]