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行为负相依随机变量阵列加权和的完全收敛性

COMPLETE CONVERGENCE OF WEIGHTED SUMS FOR ARRAYS OF NOD RANDOM VARIABLES
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摘要 本文研究了行为NOD随机变量阵列加权和的完全收敛性.运用NOD随机变量列的矩不等式以及截尾的方法,得到了关于行为NOD随机变量阵列加权和的完全收敛性的充分条件.利用获得的充分条件,推广了Baek(2008)关于行为NA随机变量阵列加权和的完全收敛性的结论,得到了比吴群英(2012)更为一般的结果. In this article,the complete convergence theorem for weighted sums for arrays of rowwise NOD random variables is investigated.By using moment inequality of negatively dependent random variables and truncation method,the sufficient conditions for complete convergence of weighted sums for arrays of NOD random variables are obtained.Using the sufficient conditions,we can promote the Bake's(2008) conclusion on complete convergence of weighted sums for arrays of NOD random variables,and we can get more general results than Wu(2012).
出处 《数学杂志》 CSCD 北大核心 2016年第4期859-866,共8页 Journal of Mathematics
基金 国家自然科学基金(11271020 11201004)资助项目 安徽省自然科学基金(1208085MA11)资助项目 安徽省高校省级自然科学研究(KJ2012ZD01)重大资助项目
关键词 NOD随机变量列 NA随机变量列 完全收敛性 矩不等式 NOD random variables NA random variables complete convergence moment inequality
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参考文献13

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二级参考文献21

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