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On Complete Convergence for an Extended Negatively Dependent Sequence

Author

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  • Xuejun Wang
  • Xiaoqin Li
  • Shuhe Hu
  • Xinghui Wang

Abstract

In this article, the Rosenthal-type maximal inequality for extended negatively dependent (END) sequence is provided. By using the Rosenthal type inequality, we present some results of complete convergence for weighted sums of END random variables under mild conditions.

Suggested Citation

  • Xuejun Wang & Xiaoqin Li & Shuhe Hu & Xinghui Wang, 2014. "On Complete Convergence for an Extended Negatively Dependent Sequence," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(14), pages 2923-2937, July.
    • Handle: RePEc:taf:lstaxx:v:43:y:2014:i:14:p:2923-2937
    DOI: 10.1080/03610926.2012.690489
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    Cited by:

    1. Liwang Ding & Ping Chen & Yongming Li, 2020. "Consistency for wavelet estimator in nonparametric regression model with extended negatively dependent samples," Statistical Papers, Springer, vol. 61(6), pages 2331-2349, December.
    2. Yan, Ji Gao, 2018. "Complete Convergence and Complete Moment Convergence for Maximal Weighted Sums of Extended Negatively Dependent Random Variables," IRTG 1792 Discussion Papers 2018-040, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Aiting Shen & Andrei Volodin, 2017. "Weak and strong laws of large numbers for arrays of rowwise END random variables and their applications," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(6), pages 605-625, November.
    4. Yi Wu & Xuejun Wang & Narayanaswamy Balakrishnan, 2020. "On the consistency of the P–C estimator in a nonparametric regression model," Statistical Papers, Springer, vol. 61(2), pages 899-915, April.

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