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Strong Convergence for Weighted Sums of Widely Orthant Dependent Random Variables and Applications

Author

Listed:
  • Yi Wu

    (Anhui University
    Chizhou University)

  • Xuejun Wang

    (Anhui University)

  • Aiting Shen

    (Anhui University)

Abstract

In this paper, the complete convergence and the Kolmogorov strong law of large numbers for weighted sums of widely orthant dependent random variables are presented. Some applications to simple linear errors-in-variables model, nonparametric regression model, and quasi-renewal counting process are provided. Simulation studies are also carried out to confirm the theoretical results.

Suggested Citation

  • Yi Wu & Xuejun Wang & Aiting Shen, 2023. "Strong Convergence for Weighted Sums of Widely Orthant Dependent Random Variables and Applications," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-28, March.
    • Handle: RePEc:spr:metcap:v:25:y:2023:i:1:d:10.1007_s11009-023-09976-3
    DOI: 10.1007/s11009-023-09976-3
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    References listed on IDEAS

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