Research article Special Issues

Almost sure convergence for a class of dependent random variables under sub-linear expectations

  • Received: 06 February 2024 Revised: 05 April 2024 Accepted: 14 May 2024 Published: 20 May 2024
  • MSC : 60F15

  • This article aimed to investigate the almost sure convergence theorem of widely negative orthant dependent (WNOD) random variables under sub-linear expectation space. The conclusions in this essay are an extension of the corresponding conclusions in the classical probability space.

    Citation: Baozhen Wang, Qunying Wu. Almost sure convergence for a class of dependent random variables under sub-linear expectations[J]. AIMS Mathematics, 2024, 9(7): 17259-17275. doi: 10.3934/math.2024838

    Related Papers:

  • This article aimed to investigate the almost sure convergence theorem of widely negative orthant dependent (WNOD) random variables under sub-linear expectation space. The conclusions in this essay are an extension of the corresponding conclusions in the classical probability space.



    加载中


    [1] S. G. Peng, G-expectation, G-Brownian motion and related stochastic calculus of Ito type, Stochast. Anal. Appl. Abel Symposium, 2006,541–567.
    [2] S. G. Peng, Multi-dimensional G-brownian motion and related stochastic calculus under gexpectation, Stochast. Proc. Appl., 118 (2008), 2223–2253. https://doi.org/10.1016/j.spa.2007.10.015 doi: 10.1016/j.spa.2007.10.015
    [3] Z. J. Chen, Strong laws of large numbers for sub-linear expectations, Sci. China Math., 59 (2016), 945–954. https://doi.org/10.1007/s11425-015-5095-0 doi: 10.1007/s11425-015-5095-0
    [4] H. Cheng, Strong laws of large numbers for sub-linear expectation under controlled 1st moment condition, Chinese Ann. Math., 39 (2018), 791–804. https://doi.org/10.1007/s11401-018-0096-2 doi: 10.1007/s11401-018-0096-2
    [5] X. Feng, Y. Lan, Strong limit theorems for arrays of rowwise independent random variables under sublinear expectation, Acta Math. Hung., 159 (2019), 299–322. https://doi.org/10.1007/s10474-019-00938-1 doi: 10.1007/s10474-019-00938-1
    [6] H. Cheng, A strong law of large numbers for sub-linear expectation under a general moment condition, Stat. Probab. Lett., 119 (2016), 248–258. https://doi.org/10.1016/j.spl.2016.08.015 doi: 10.1016/j.spl.2016.08.015
    [7] Q. Y. Wu, Y. Y. Jiang, Strong law of large numbers and Chover's law of the iterated logarithm under sub-linear expectations, J. Math. Anal. Appl., 460 (2018), 252–270. https://doi.org/10.1016/j.jmaa.2017.11.053 doi: 10.1016/j.jmaa.2017.11.053
    [8] X. Y. Chen, F. Liu, Strong laws of large numbers for negatively dependent random variables under sublinea rexpectations, Commun. Stat. Theory Meth., 46 (2017), 12387–12400. https://doi.org/10.1080/03610926.2017.1300274 doi: 10.1080/03610926.2017.1300274
    [9] M. M. Gao, F. Hu, J. B. Sun, A strong law of large number for negatively dependent and non identical distributed random variables in the framework of sublinear expectation, Commun. Stat. Theory Meth., 48 (2019), 5058–5073. https://doi.org/10.1080/03610926.2018.1508708 doi: 10.1080/03610926.2018.1508708
    [10] Z. W. Liang, Q. Y. Wu, Several Different types of convergence for ND random variables under sublinear expectations, Discrete Dyn. Nat. Soc., 2021 (2021), 6653435. https://doi.org/10.1155/2021/6653435 doi: 10.1155/2021/6653435
    [11] L. X. Zhang, Exponential inequalities for under the sub-linear expectations with applications to laws of the iterated logarithm, Sci. China Math., 59 (2016), 2503–2526. https://doi.org/10.1007/s11425-016-0079-1 doi: 10.1007/s11425-016-0079-1
    [12] R. X. Wang, Q. Y. Wu, Some types of convergence for negatively dependent random variables under sublinear expectations, Discrete Dyn. Nat. Soc., 2019 (2019), 9037258. https://doi.org/10.1155/2019/9037258 doi: 10.1155/2019/9037258
    [13] X. W. Feng, Law of the logarithm for weighted sums of negatively dependent random variables under sublinear expectation, Stat. Probab. Lett., 149 (2019), 132–141. https://doi.org/10.1016/j.spl.2019.01.033 doi: 10.1016/j.spl.2019.01.033
    [14] L. X. Zhang, Strong limit theorems for extended independent and extended negatively dependent random variables under sub-linear expectations, Acta Math. Sci., 42 (2022), 467–490. https://doi.org/10.1007/s10473-022-0203-z doi: 10.1007/s10473-022-0203-z
    [15] L. Wang, Q. Y. Wu, Almost sure convergence theorems for arrays under sub-linear expectations, AIMS Math., 7 (2022), 17767–17784. https://doi.org/10.3934/math.2022978 doi: 10.3934/math.2022978
    [16] Y. W. Lin, X. W. Feng, Complete convergence and strong law of large numbers for arrays of random variables under sublinear expectations, Commun. Stat. Theory Meth., 49 (2020), 5866–5882. https://doi.org/10.1080/03610926.2019.1625924 doi: 10.1080/03610926.2019.1625924
    [17] K. S. Hwang, Almost sure convergence of weighted sums for widely negative dependent random variables under sub-linear expectations, Adv. Stud. Contemp. Math., 32 (2022), 463–475.
    [18] K. K. Anna, Complete convergence and complete moment convergence for widely negative orthant dependent random variables under the sub-linear expectations, Stochastics, 95 (2023), 1101–1119. https://doi.org/10.1080/17442508.2022.2164695 doi: 10.1080/17442508.2022.2164695
    [19] J. G. Yan, Almost sure convergence for weighted sums of WNOD random variables and its applications to non parametric regression models, Commun. Stat. Theory Meth., 47 (2018), 3893–3909 https://doi.org/10.1080/03610926.2017.1364390 doi: 10.1080/03610926.2017.1364390
    [20] E. Seneta, Regularly Varying Functions, Berlin: Springer, 1976.
  • Reader Comments
  • © 2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(544) PDF downloads(31) Cited by(0)

Article outline

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog