Strong laws for weighted sums of widely orthant dependent random variables and applications
Abstract: In this study, the strong law of large numbers and the convergence rate for weighted sums of non-identically distributed widely orthant dependent random variables are established. As applications, the strong consistency for weighted estimator in nonparametric regression model and the rate of strong consistency for least-squares estimator in multiple linear regression model are obtained. Some numerical simulations are also provided to verify the validity of the theoretical results.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Strong laws for weighted sums of widely orthant dependent random variables and applications ; volume:22 ; number:1 ; year:2024 ; extent:14
Open mathematics ; 22, Heft 1 (2024) (gesamt 14)
- Creator
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Zhu, Yong
Wang, Wei
Chen, Kan
- DOI
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10.1515/math-2024-0027
- URN
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urn:nbn:de:101:1-2408311547159.723502394643
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:38 AM CEST
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Associated
- Zhu, Yong
- Wang, Wei
- Chen, Kan
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