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Sibirskie Èlektronnye Matematicheskie Izvestiya [Siberian Electronic Mathematical Reports], 2024, Volume 21, Issue 2, Pages 1450–1459 DOI: https://doi.org/10.33048/semi.2024.21.092
(Mi semr1755)
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This article is cited in 1 scientific paper (total in 1 paper)
Probability theory and mathematical statistics
On the accuracy of the uniform approximation of universal local constant kernel estimators to smooth regression functions
Y. Y. Linke Sobolev Institute of Mathematics, pr. Koptyuga, 4, 630090, Novosibirsk, Russia
DOI:
https://doi.org/10.33048/semi.2024.21.092
Abstract:
The paper considers universal locally constant kernel estimators in nonparametric regression. Previously, these estimators were studied only in the case of a continuous regression function. It is shown that with the additional condition of smoothness of the regression function, the accuracy of the uniform approximation can be improved.
Keywords:
nonparametric regression, universal local constant kernel estimator, uniform consistency, fixed design, random design.
Received October 20, 2024, published December 25, 2024
Citation:
Y. Y. Linke, “On the accuracy of the uniform approximation of universal local constant kernel estimators to smooth regression functions”, Sib. Èlektron. Mat. Izv., 21:2 (2024), 1450–1459
Linking options:
https://www.mathnet.ru/eng/semr1755 https://www.mathnet.ru/eng/semr/v21/i2/p1450
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| Statistics & downloads: |
| Abstract page: | 101 | | Full-text PDF : | 55 | | References: | 6 |
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