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Research Article | Open Access

Complete convergence and complete moment convergence for maximal weighted sums of extended negatively dependent random variables under sub-linear expectations

School of Information Engineering, Jingdezhen Ceramic University, Jingdezhen, 333403, China
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Abstract

In this article, we study the complete convergence and complete moment convergence for maximal weighted sums of extended negatively dependent random variables under sub-linear expectations. We also give some sufficient assumptions for the convergence. Moreover, we get the Marcinkiewicz-Zygmund type strong law of large numbers for weighted sums of extended negatively dependent random variables. The results obtained in this paper generalize the relevant ones in probability space.

Keywords

extended negatively dependentcomplete convergencecomplete moment convergencemaximal weighted sumssub-linear expectations
CLC number: 60F05, 60F15

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AIMS Mathematics
Volume 8 Issue 8,
August 2023
Pages 19442-19460
DOI: 10.3934/math.2023992

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Cite this article:
Xu M. Complete convergence and complete moment convergence for maximal weighted sums of extended negatively dependent random variables under sub-linear expectations. AIMS Mathematics, 2023, 8(8): 19442-19460. https://doi.org/10.3934/math.2023992

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Received: 10 April 2023
Revised: 17 May 2023
Accepted: 28 May 2023
Published: 15 August 2023
©2023 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)