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Strong convergence for weighted sums of END random variables under the sub-linear expectations

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  • Fengxiang Feng
  • Haiwu Huang

Abstract

In this article, we study strong limit theorems for weighted sums of extended negatively dependent (END, for short) random variables under the sub-linear expectations. We establish some general complete convergence theorems for weighted sums of END random variables under the sub-linear expectations. Our results partly generalize and improve the corresponding ones previously obtained by Cai (Metrika, 68:323-331, 2008), Huang and Wang (J. Inequal. Appl. 233, doi:10.1186/1029-242X-2012-233, 2012) and Wang et al. (RACSAM, 106:235-245, 2012) in the classical probability space to the sub-linear expectation space under weaker moment conditions.

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  • Fengxiang Feng & Haiwu Huang, 2021. "Strong convergence for weighted sums of END random variables under the sub-linear expectations," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 51(22), pages 7885-7896, September.
    • Handle: RePEc:taf:lstaxx:v:51:y:2021:i:22:p:7885-7896
    DOI: 10.1080/03610926.2021.1883654
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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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