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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)
 

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
Full-text PDF (423 kB) Citations (1)
References:
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.
Funding agency Grant number
Ministry of Science and Higher Education of the Russian Federation FWNF-2024-0001
Received October 20, 2024, published December 25, 2024
Document Type: Article
UDC: 519.234
MSC: 62G08
Language: Russian
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
Citation in format AMSBIB
\Bibitem{Lin24}
\by Y.~Y.~Linke
\paper On the accuracy of the uniform approximation of universal local constant kernel estimators to smooth regression functions
\jour Sib. \`Elektron. Mat. Izv.
\yr 2024
\vol 21
\issue 2
\pages 1450--1459
\mathnet{http://mi.mathnet.ru/semr1755}
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  • https://www.mathnet.ru/eng/semr/v21/i2/p1450
  • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
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