On the strong convergence properties for weighted sums of negatively orthant dependent random variables

2018 ◽  
Vol 33 (1) ◽  
pp. 35-47
Author(s):  
Xin Deng ◽  
Xu-fei Tang ◽  
Shi-jie Wang ◽  
Xue-jun Wang
2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Qingxia Zhang ◽  
Dingcheng Wang

Let{Xni;i≥1,n≥1}be an array of rowwise negatively orthant dependent (NOD) random variables. The authors discuss the rate of strong convergence for weighted sums of arrays of rowwise NOD random variables and solve an open problem posed by Huang and Wang (2012).


2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Jiangfeng Wang ◽  
Qunying Wu

Some strong laws of large numbers and strong convergence properties for arrays of rowwise negatively associated and linearly negative quadrant dependent random variables are obtained. The results obtained not only generalize the result of Hu and Taylor to negatively associated and linearly negative quadrant dependent random variables, but also improve it.


2017 ◽  
Vol 67 (1) ◽  
pp. 235-244
Author(s):  
Aiting Shen ◽  
Yu Zhang ◽  
Andrei Volodin

Abstract Let {Xni , i ≥ 1, n ≥1} be an array of rowwise negatively orthant dependent random variables which is stochastically dominated by a random variable X. Wang et al. [15. Complete convergence for arrays of rowwise negatively orthant dependent random variables, RACSAM, 106 (2012), 235–245] studied the complete convergence for arrays of rowwise negatively orthant dependent random variables under the condition that X has an exponential moment, which seems too strong. We will further study the complete convergence for arrays of rowwise negatively orthant dependent random variables under the condition that X has a moment, which is weaker than exponential moment. Our results improve the corresponding ones of Wang et al. [15].


2013 ◽  
Vol 2013 ◽  
pp. 1-12
Author(s):  
Zhiyong Chen ◽  
Shuhe Hu ◽  
Jimin Ling ◽  
Xuejun Wang

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