Complete moment convergence of widely orthant dependent random variables

2017 ◽  
Vol 46 (14) ◽  
pp. 7256-7265 ◽  
Author(s):  
Xi Liu ◽  
Yan Shen ◽  
Jie Yang ◽  
Yamei Lu
Keyword(s):  
Random Variables ◽  
Complete Moment Convergence ◽  
Dependent Random Variables ◽  
Moment Convergence ◽  
Widely Orthant Dependent

scholarly journals On complete and complete moment convergence for weighted sums of widely orthant dependent random variables

Filomat ◽  
2018 ◽  
Vol 32 (15) ◽  
pp. 5347-5359 ◽  
Author(s):  
Caoqing Wu ◽  
Mingming Ning ◽  
Aiting Shen
Keyword(s):  
Complete Convergence ◽  
Random Variables ◽  
Weighted Sums ◽  
Complete Moment Convergence ◽  
Dependent Random Variables ◽  
Moment Convergence ◽  
Identical Distribution ◽  
Widely Orthant Dependent

In this article, the complete convergence for weighted sums of widely orthant dependent (WOD, in short) random variables without identical distribution is investigated. In addition, the complete moment convergence for weighted sums of WOD random variables is also obtained. The results obtained in the paper generalize some corresponding ones for some 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.

Complete moment convergence forweighted sums of pairwise negatively quadrant dependent random variables

Filomat ◽  
2020 ◽  
Vol 34 (10) ◽  
pp. 3459-3471
Author(s):  
Mingming Zhao ◽  
Shengnan Ding ◽  
Di Zhang ◽  
Xuejun Wang
Keyword(s):  
Theoretical Result ◽  
Sufficient Conditions ◽  
Random Variables ◽  
Weighted Sums ◽  
Complete Moment Convergence ◽  
Dependent Random Variables ◽  
Moment Convergence

In this article, the complete moment convergence for weighted sums of pairwise negatively quadrant dependent (NQD, for short) random variables is studied. Several sufficient conditions to prove the complete moment convergence for weighted sums of NQD random variables are presented. The results obtained in the paper extend some corresponding ones in the literature. The simulation is also presented which can verify the validity of the theoretical result.

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