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Complete convergence for m-widely acceptable random variables under sub-linear expectations

Communications in Statistics - Theory and Methods
. In this work, we study the complete convergence for arrays of rowwise m-widely acceptable random variables under sub-linear expectations. Some general results are established, which extend and improve some existing ones in sub-linear expectation space.
Hui Wang, Wei Wang, Yi Wu
semanticscholar   +1 more source

Complete convergence for weighted sums of widely negative orthant dependent random variables under the sub-linear expectations

Communications in Statistics - Theory and Methods
. In this article, we study and establish complete convergence for widely negative orthant dependent random variables under the sub-linear expectations, which extend some complete convergence theorems for widely negative orthant dependent random ...
Lizhen Huang, Qun-Ying Wu
semanticscholar   +1 more source

The convergence properties for randomly weighted sums of widely negative dependent random variables under sub-linear expectations with related statistical applications

Statistics (Berlin)
In this paper, we study the complete convergence and complete moment convergence for randomly weighted sums of arrays of rowwise widely negative dependent random variables in sub-linear expectation space under some appropriate conditions, which extend ...
Miaomiao Wang   +2 more
semanticscholar   +1 more source

Central Limit Theorem for Linear Processes Generated by m-Dependent Random Variables Under the Sub-Linear Expectation

Communications in Statistics - Theory and Methods, 2023
Yong Zhang, Shuang Guo
exaly  

On the Laws of the Iterated Logarithm Under Sub-Linear Expectations

Probability, Uncertainty and Quantitative Risk, 2021
Li-Xin Zhang
exaly  

General Results on Precise Asymptotics Under Sub-Linear Expectations

Journal of Mathematical Analysis and Applications, 2022
exaly  

Complete Convergence Theorem for Negatively Dependent Random Variables Under Sub-Linear Expectations

Communications in Statistics - Theory and Methods, 2022
Qunying Wu, Bin-xia CHEN
exaly  

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