Strong laws of large numbers for negatively dependent random variables under sublinear expectations

2017 ◽  
Vol 46 (24) ◽  
pp. 12387-12400 ◽  
Author(s):  
Xiaoyan Chen ◽  
Fang Liu
Keyword(s):  
Random Variables ◽  
Dependent Random Variables ◽  
Laws Of Large Numbers ◽  
Strong Laws ◽  
Negatively Dependent Random Variables ◽  
Large Numbers

scholarly journals Strong Laws of Large Numbers for Arrays of Rowwise NA and LNQD Random Variables

2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Jiangfeng Wang ◽  
Qunying Wu
Keyword(s):  
Strong Convergence ◽  
Random Variables ◽  
Convergence Properties ◽  
Dependent Random Variables ◽  
Laws Of Large Numbers ◽  
Negatively Associated ◽  
Strong Laws ◽  
Large Numbers

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.

scholarly journals On exact strong laws of large numbers under general dependence conditions

2018 ◽  
Vol 38 (1) ◽  
pp. 103-121 ◽  
Author(s):  
André Adler ◽  
Przemysław Matuła
Keyword(s):  
Random Variables ◽  
Almost Sure Convergence ◽  
Weighted Sums ◽  
Dependent Random Variables ◽  
Laws Of Large Numbers ◽  
Associated Random Variables ◽  
Negatively Associated ◽  
Strong Laws ◽  
Large Numbers ◽  
Dependence Conditions

We study the almost sure convergence of weighted sums of dependent random variables to a positive and finite constant, in the case when the random variables have either mean zero or no mean at all. These are not typical strong laws and they are called exact strong laws of large numbers. We do not assume any particular type of dependence and furthermore consider sequences which are not necessarily identically distributed. The obtained results may be applied to sequences of negatively associated random variables.

scholarly journals Weak laws of large numbers for arrays of rowwise negatively dependent random variables

2001 ◽  
Vol 14 (3) ◽  
pp. 227-236 ◽  
Author(s):  
R. L. Taylor ◽  
R. F. Patterson ◽  
A. Bozorgnia
Keyword(s):  
Random Variables ◽  
Negative Dependence ◽  
Dependent Random Variables ◽  
Moment Conditions ◽  
General Hypothesis ◽  
Laws Of Large Numbers ◽  
Negatively Dependent Random Variables ◽  
Large Numbers ◽  
Weak Laws ◽  
The Moment

Weak laws of large numbers for arrays of rowwise negatively dependent random variables are obtained in this paper. The more general hypothesis of negative dependence relaxes the usual assumption of independence. The moment conditions are similar to previous results, and the stochastic bounded condition also provides a generalization of the usual distributional assumptions.

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