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On Complete Convergence in Marcinkiewicz-Zygmund Type SLLN for END Random Variables and Its Applications

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  • Jigao Yan

Abstract

In this paper, the complete convergence for maximal weighted sums of extended negatively dependent (END, for short) random variables is investigated. Some sufficient conditions for the complete convergence and some applications to a nonparametric model are provided. The results obtained in the paper generalize and improve the corresponding ones of Wang et al. (2014b) and Shen, Xue, and Wang (2017).

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  • Jigao Yan, 2019. "On Complete Convergence in Marcinkiewicz-Zygmund Type SLLN for END Random Variables and Its Applications," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(20), pages 5074-5098, October.
    • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:20:p:5074-5098
    DOI: 10.1080/03610926.2018.1508709
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    Cited by:

    1. Jin Yu Zhou & Ji Gao Yan & Fei Du, 2023. "Complete and Complete f -Moment Convergence for Arrays of Rowwise END Random Variables and Some Applications," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(2), pages 1307-1330, August.
    2. Jinyu Zhou & Jigao Yan & Dongya Cheng, 2024. "Strong consistency of tail value-at-risk estimator and corresponding general results under widely orthant dependent samples," Statistical Papers, Springer, vol. 65(6), pages 3357-3394, August.

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