Some strong limit theorems of weighted sums for negatively dependent generalized Gaussian random variables

2007 ◽  
Vol 77 (11) ◽  
pp. 1106-1110 ◽  
Author(s):  
M. Amini ◽  
H. Zarei ◽  
A. Bozorgnia
Keyword(s):  
Limit Theorems ◽  
Random Variables ◽  
Weighted Sums ◽  
Strong Limit ◽  
Gaussian Random Variables

scholarly journals On strong limit theorems for negatively superadditive dependent random variables

Filomat ◽  
2015 ◽  
Vol 29 (7) ◽  
pp. 1541-1547
Author(s):  
Yongjun Zhang
Keyword(s):  
Strong Convergence ◽  
Limit Theorems ◽  
Complete Convergence ◽  
Convergence Property ◽  
Sufficient Conditions ◽  
Random Variables ◽  
Weighted Sums ◽  
Strong Limit ◽  
Nsd Random Variables ◽  
Independent Identically Distributed

In this paper, we obtain strong convergence property for Jamison weighted sums of negatively superadditive dependent (NSD, in short) random variables, which extends the famous Jamison theorem. In addition, some sufficient conditions for complete convergence for weighed sums of NSD random variables are presented. These results generalize the corresponding results for independent identically distributed random variables to the case of NSD random variables without assumption of identical distribution.

scholarly journals Complete integration convergence for arrays of rowwise extended negatively dependent random variables under the sub-linear expectations

2021 ◽  
Vol 6 (11) ◽  
pp. 12166-12181
Author(s):  
Shuyan Li ◽  
◽  
Qunying Wu
Keyword(s):  
Limit Theorems ◽  
Probability Space ◽  
Random Variables ◽  
Weighted Sums ◽  
Complete Moment Convergence ◽  
Dependent Random Variables ◽  
Complete Integration ◽  
Moment Convergence ◽  
Negatively Dependent Random Variables

<abstract><p>Limit theorems of sub-linear expectations are challenging field that has attracted widespread attention in recent years. In this paper, we establish some results on complete integration convergence for weighted sums of arrays of rowwise extended negatively dependent random variables under sub-linear expectations. Our results generalize the complete moment convergence of the probability space to the sub-linear expectation space.</p></abstract>

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.

Sign in / Sign up

Export Citation Format

Share Document