吉林大学学报(理学版) ›› 2021, Vol. 59 ›› Issue (5): 1101-1106.

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 NSD随机阵列加权和最大值的收敛性

胡学平, 王柳柳, 杨瑞   

  1. 安庆师范大学 数理学院, 安徽 安庆 246133
  • 收稿日期:2021-04-12 出版日期:2021-09-26 发布日期:2021-09-26
  • 通讯作者: 胡学平 E-mail:hxprob@163.com

Convergence Properties for Maximum Weighted Sums of NSD Random Arrays

HU Xueping, WANG Liuliu, YANG Rui   

  1. School of Mathematics and Physics, Anqing Normal University, Anqing 246133, Anhui Province, China
  • Received:2021-04-12 Online:2021-09-26 Published:2021-09-26

摘要: 利用负超可加相依(NSD)随机阵列的Rosenthal型矩不等式和截尾方法, 在随机阵列{Xnk, 1≤k≤kn, n≥1}关于{ank, 1≤k≤kn, n≥1}一致可积的条件下, 讨论NSD随机阵列加权和最大值的弱收敛、 Lr收敛和完全收敛性.

关键词: NSD随机阵列, 一致可积, 弱收敛, Lr收敛, 完全收敛

Abstract: By utilizing the Rosenthal moment inequality of negatively superadditive dependent (NSD) random arrays and truncated method, 
we discussed  the weak convergence, the Lr convergence and the complete convergence for maximum weighted sums of NSD random arrays under the condition of {Xnk, 1≤k≤kn, n≥1} on {ank, 1≤k≤kn, n≥1} uniform integrability.

Key words: NSD random arrays; , uniform integrability, weak convergence, Lr convergence, complete convergence

中图分类号: 

  • O211.4