Central limit theorem for linear processes generated by <i>m</i>-dependent random variables under the sub-linear expectation-Reference-Cited by-同舟云学术

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Central limit theorem for linear processes generated by m-dependent random variables under the sub-linear expectation

Published:2022-01-24 Issue: Volume: Page:1-13
ISSN:0361-0926
Container-title:Communications in Statistics - Theory and Methods
language:en
Short-container-title:Communications in Statistics - Theory and Methods

Author:

Guo Shuang¹,Zhang Yong¹

Affiliation:

1. School of Mathematics, Jilin University, Changchun, China

Funder

National Natural Science Foundation of China

Science and Technology Development Program of Jilin Province

Science and Technology Program of Jilin Educational Department during the “13th Five-Year” Plan Period

Fundamental Research Funds for the Central Universities

Publisher

Informa UK Limited

Subject

Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610926.2022.2028840

Reference27 articles.

1. The central limit theorem for m-dependent variables

2. A general form for precise asymptotics for complete convergence under sublinear expectation

3. Complete and complete moment convergence for weighted sums of arrays of rowwise negatively dependent random variables under the sub-linear expectations

4. The central limit theorem for dependent random variables

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1. Complete convergence for moving average process generated by extended negatively dependent random variables under sub-linear expectations;Communications in Statistics - Theory and Methods;2023-11-19

2. Equivalent Conditions of Complete p-th Moment Convergence for Weighted Sum of ND Random Variables under Sublinear Expectation Space;Mathematics;2023-08-13

3. Moderate Deviation Principle for Linear Processes Generated by Dependent Sequences under Sub-Linear Expectation;Axioms;2023-08-11

4. Precise asymptotics for complete integral convergence in the law of the logarithm under the sub-linear expectations;AIMS Mathematics;2023

5. Strong law of large numbers for linear processes under sublinear expectation;Communications in Statistics - Theory and Methods;2022-09-19

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