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Strong laws of large numbers for weighted sums of extended negatively dependent random variables under sub-linear expectations

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  • Zhouting Zhan
  • Qunying Wu

Abstract

In this paper, we study strong laws of large numbers for weighted sums of extended negatively dependent random variables under sub-linear expectation space. As an application, several results on strong laws of large numbers of ∑i=1knaniXi with the condition of kn↑∞ and kn=∞ for the double arrays of positive real numbers {ani;1≤i≤kn,n≥1} and sequences of extended negatively dependent random variables have been established in sub-linear expectations. The main results obtained in this article are the extensions of strong laws of large numbers for weighted sums of negatively dependent random variables under the traditional probability space.

Suggested Citation

  • Zhouting Zhan & Qunying Wu, 2022. "Strong laws of large numbers for weighted sums of extended negatively dependent random variables under sub-linear expectations," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 51(5), pages 1197-1216, March.
    • Handle: RePEc:taf:lstaxx:v:51:y:2022:i:5:p:1197-1216
    DOI: 10.1080/03610926.2021.1873380
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    Cited by:

    1. Shuxia Guo & Zhe Meng, 2023. "The Marcinkiewicz–Zygmund-Type Strong Law of Large Numbers with General Normalizing Sequences under Sublinear Expectation," Mathematics, MDPI, vol. 11(23), pages 1-21, November.

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