scholarly journals Erratum: Complete Convergence Theorems for Extended Negatively Dependent Random Variables, By Tien-Chung Hu, Andrew Rosalsky, and Kuo-Lung Wang, Sankhyā Series A, Vol. 77, Part 1, 1-29, 2015

Sankhya A ◽  
2016 ◽  
Vol 78 (2) ◽  
pp. 347-348
Author(s):  
Tien-Chung Hu ◽  
Kuo-Lung Wang ◽  
Andrew Rosalsky
Keyword(s):  
Complete Convergence ◽  
Random Variables ◽  
Convergence Theorems ◽  
Dependent Random Variables ◽  
Negatively Dependent Random Variables

scholarly journals Complete convergence and complete moment convergence for negatively dependent random variables under sub-linear expectations

Filomat ◽  
2020 ◽  
Vol 34 (4) ◽  
pp. 1093-1104
Author(s):  
Qunying Wu ◽  
Yuanying Jiang
Keyword(s):  
Probability Space ◽  
Complete Convergence ◽  
Random Variables ◽  
Complete Moment Convergence ◽  
Convergence Theorems ◽  
Dependent Random Variables ◽  
Moment Convergence ◽  
Negatively Dependent Random Variables

This paper we study and establish the complete convergence and complete moment convergence theorems under a sub-linear expectation space. As applications, the complete convergence and complete moment convergence for negatively dependent random variables with CV (exp (ln? |X|)) < ?, ? > 1 have been generalized to the sub-linear expectation space context. We extend some complete convergence and complete moment convergence theorems for the traditional probability space to the sub-linear expectation space. Our results generalize corresponding results obtained by Gut and Stadtm?ller (2011), Qiu and Chen (2014) and Wu and Jiang (2016). There is no report on the complete moment convergence under sub-linear expectation, and we provide the method to study this subject.

scholarly journals Some Types of Convergence for Negatively Dependent Random Variables under Sublinear Expectations

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Ruixue Wang ◽  
Qunying Wu
Keyword(s):  
Probability Space ◽  
Complete Convergence ◽  
Random Variables ◽  
Almost Sure Convergence ◽  
Weighted Sums ◽  
Convergence Theorems ◽  
Dependent Random Variables ◽  
Sublinear Expectation ◽  
Negatively Dependent Random Variables

In this paper, we research complete convergence and almost sure convergence under the sublinear expectations. As applications, we extend some complete and almost sure convergence theorems for weighted sums of negatively dependent random variables from the traditional probability space to the sublinear expectation space.

scholarly journals Complete Convergence for Weighted Sums of Sequences of Negatively Dependent Random Variables

2011 ◽  
Vol 2011 ◽  
pp. 1-16 ◽  
Author(s):  
Qunying Wu
Keyword(s):  
Complete Convergence ◽  
Random Variables ◽  
Weighted Sums ◽  
Moment Inequality ◽  
Convergence Theorems ◽  
Dependent Random Variables ◽  
Negatively Dependent Random Variables ◽  
The Moment

Applying to the moment inequality of negatively dependent random variables the complete convergence for weighted sums of sequences of negatively dependent random variables is discussed. As a result, complete convergence theorems for negatively dependent sequences of random variables are extended.

On Complete Convergence for Arrays of Rowwise Negatively Dependent Random Variables

2015 ◽  
Vol 18 (3) ◽  
pp. 283-292
Author(s):  
Ming Hua Shi ◽  
Jiang Dong Zhao ◽  
Xiao Yu Chen ◽  
Yong Chao Dong
Keyword(s):  
Complete Convergence ◽  
Random Variables ◽  
Dependent Random Variables ◽  
Negatively Dependent Random Variables
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