Strong convergence for weighted sums of END random variables under the sub-linear expectations

2021 ◽  
pp. 1-12
Author(s):  
Fengxiang Feng ◽  
Haiwu Huang
Keyword(s):  
Strong Convergence ◽  
Random Variables ◽  
Weighted Sums ◽  
End Random Variables

scholarly journals On Some Conditions for Strong Law of Large Numbers for Weighted Sums of END Random Variables under Sublinear Expectations

2019 ◽  
Vol 2019 ◽  
pp. 1-8
Author(s):  
Xiaochen Ma ◽  
Qunying Wu
Keyword(s):  
Probability Space ◽  
Law Of Large Numbers ◽  
Random Variables ◽  
Weighted Sums ◽  
Dependent Random Variables ◽  
Strong Law ◽  
Sublinear Expectation ◽  
Negatively Dependent Random Variables ◽  
Large Numbers ◽  
End Random Variables

In this article, we research some conditions for strong law of large numbers (SLLNs) for weighted sums of extended negatively dependent (END) random variables under sublinear expectation space. Our consequences contain the Kolmogorov strong law of large numbers and the Marcinkiewicz strong law of large numbers for weighted sums of extended negatively dependent random variables. Furthermore, our results extend strong law of large numbers for some sequences of random variables from the traditional probability space to the sublinear expectation space context.

scholarly journals A Note on the Rate of Strong Convergence for Weighted Sums of Arrays of Rowwise Negatively Orthant Dependent Random Variables

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Qingxia Zhang ◽  
Dingcheng Wang
Keyword(s):  
Strong Convergence ◽  
Open Problem ◽  
Random Variables ◽  
Weighted Sums ◽  
Dependent Random Variables

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).

scholarly journals Negative dependence for fuzzy random variables: Basic definitions and some limit theorems

Filomat ◽  
2016 ◽  
Vol 30 (9) ◽  
pp. 2535-2549 ◽  
Author(s):  
H. Ahmadzade ◽  
M. Amini ◽  
S.M. Taheri ◽  
A. Bozorgnia
Keyword(s):  
Strong Convergence ◽  
Limit Theorems ◽  
Random Variables ◽  
Weighted Sums ◽  
Negative Dependence ◽  
Fuzzy Random Variables ◽  
Weak And Strong Convergence ◽  
Basic Properties ◽  
Direct Extension ◽  
Fuzzy Random

The concept of negative dependence for fuzzy random variables is introduced. The basic properties of such random variables are investigated. Some results on weak and strong convergence for sums and weighted sums of pairwise negatively dependent fuzzy random variables are derived. As a direct extension of classical methods, some limit theorems are established based on the concept of variance and covariance.

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