Strong convergence for weighted sums of arrays of rowwise pairwise NQD random variables

2013 ◽  
Vol 65 (1) ◽  
pp. 119-130 ◽  
Author(s):  
Yongfeng Wu
Keyword(s):  
Strong Convergence ◽  
Random Variables ◽  
Weighted Sums

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.

scholarly journals A note on the strong convergence for weighted sums of ρ^*-mixing random variables

2018 ◽  
pp. 507-516
Author(s):  
Haiwu Huang ◽  
Hang Zou ◽  
Yanh ng Feng ◽  
Fengxi ng Feng
Keyword(s):  
Strong Convergence ◽  
Random Variables ◽  
Weighted Sums ◽  
Mixing Random Variables

On the strong convergence forweighted sums of negatively superadditive dependent random variables

Filomat ◽  
2017 ◽  
Vol 31 (2) ◽  
pp. 295-308
Author(s):  
Lulu Zheng ◽  
Xuejun Wang ◽  
Wenzhi Yang
Keyword(s):  
Strong Convergence ◽  
Complete Convergence ◽  
Random Variables ◽  
Maximal Inequality ◽  
Weighted Sums ◽  
Exponential Inequality ◽  
Associated Random Variables ◽  
Negatively Associated ◽  
Identical Distribution ◽  
Nsd Random Variables

In this paper, we present some results on the complete convergence for arrays of rowwise negatively superadditive dependent (NSD, in short) random variables by using the Rosenthal-type maximal inequality, Kolmogorov exponential inequality and the truncation method. The results obtained in the paper extend the corresponding ones for weighted sums of negatively associated random variables with identical distribution to the case of arrays of rowwise NSD random variables without identical distribution.

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