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

Yi Wu, Xuejun Wang and Aiting Shen ()
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Yi Wu: Anhui University
Xuejun Wang: Anhui University
Aiting Shen: Anhui University

Methodology and Computing in Applied Probability, 2023, vol. 25, issue 1, 1-28

Abstract: 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.

Keywords: Widely orthant dependent random variables; Complete convergence; Strong law of large numbers; Simple linear errors-in-variables model; Nonparametric regression model; Quasi-renewal counting process; 60F15; 62G05; 62G20; 62K05 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11009-023-09976-3

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