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Complete moment convergence for randomly weighted sums of END sequences and its applications

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  • Xiu Xu
  • Jigao Yan

Abstract

In this article, some results on the complete moment convergence for maximal randomly weighted sums of extended negatively dependent (END) random variables are established. In some senses, the results obtained in this article extend the corresponding ones of in reference. As an application of the main results, we consider a result on complete consistency for the weighted estimator in a non parametric regression model based on END errors. We also give a simulation to verify the validity of the theoretical result.

Suggested Citation

  • Xiu Xu & Jigao Yan, 2021. "Complete moment convergence for randomly weighted sums of END sequences and its applications," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(12), pages 2877-2899, June.
    • Handle: RePEc:taf:lstaxx:v:50:y:2021:i:12:p:2877-2899
    DOI: 10.1080/03610926.2019.1678637
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    Cited by:

    1. Thomas Hitchen & Saralees Nadarajah, 2024. "Exact Results for the Distribution of Randomly Weighted Sums," Mathematics, MDPI, vol. 12(1), pages 1-22, January.
    2. 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.

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