逐行负相关随机变量数组加权和的完全矩收敛性

Pub Date : 2014-05-04 DOI:10.1080/17442508.2013.801971
M. Guo
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引用次数: 9

摘要

负相关随机变量(NA)是一类更一般的随机变量,它包括一组独立的随机变量,已被应用于许多实际领域。本文研究了逐行NA随机变量数组的加权和的完全矩收敛性。建立了行NA随机变量阵列加权和矩完全收敛的几个充分条件。此外,在较弱的条件下,我们推广了Baek等人的结果。韩国社会科学,37(2008),第73-80页。达成。肛[j]. 2011(2011)。作为应用,得到了基于NA随机序列的移动平均过程的完全矩收敛性,改进了Li和Zhang [Stat. Probab]的结果。左70(2004),第191-197页]。
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On complete moment convergence of weighted sums for arrays of row-wise negatively associated random variables
Negatively associated (NA) random variables are a more general class of random variables which include a set of independent random variables and have been applied to many practical fields. In this paper, the complete moment convergence of weighted sums for arrays of row-wise NA random variables is investigated. Some sufficient conditions for complete moment convergence of weighted sums for arrays of row-wise NA random variables are established. Moreover, under the weaker conditions, we extend the results of Baek et al. [J. Korean Stat. Soc. 37 (2008), pp. 73–80] and Sung [Abstr. Appl. Anal. 2011 (2011)]. As an application, the complete moment convergence of moving average processes based on an NA random sequence is obtained, which improves the result of Li and Zhang [Stat. Probab. Lett. 70 (2004), pp. 191–197 ].
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