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Matematicheskie Trudy, 2023, Volume 26, Number 2, Pages 177–191
DOI: https://doi.org/10.33048/mattrudy.2023.26.209
(Mi mt685)
 

This article is cited in 3 scientific papers (total in 3 papers)

An approach to constructing explicit estimators in nonlinear regression

Yu. Yu. Linke, I. S. Borisov

Sobolev Institute of Mathematics, Novosibirsk, 630090, Russia
References:
DOI: https://doi.org/10.33048/mattrudy.2023.26.209
Abstract: We consider the problem of constructing explicit consistent estimators of finite-dimensional parameters of nonlinear regression models using various nonparametric kernel estimators.
Key words: nonlinear regression, nonparametric regression, kernel estimators, uniform consistency, fixed regressors, random regressors.
Funding agency Grant number
Ministry of Science and Higher Education of the Russian Federation FWNF-2022-0015
The work was carried out within the State Task for the Sobolev Institute of Mathematics (project no. FWNF-2022-0015).
Received: 13.07.2023
Revised: 01.10.2023
Accepted: 05.10.2023
English version:
Siberian Advances in Mathematics, 2023, Volume 33, Issue 4, Pages 338–346
DOI: https://doi.org/10.1134/S1055134423040065
Document Type: Article
UDC: 519.23
Language: Russian
Citation: Yu. Yu. Linke, I. S. Borisov, “An approach to constructing explicit estimators in nonlinear regression”, Mat. Tr., 26:2 (2023), 177–191; Siberian Adv. Math., 33:4 (2023), 338–346
Citation in format AMSBIB
\Bibitem{LinBor23}
\by Yu.~Yu.~Linke, I.~S.~Borisov
\paper An approach to constructing explicit estimators in nonlinear regression
\jour Mat. Tr.
\yr 2023
\vol 26
\issue 2
\pages 177--191
\mathnet{http://mi.mathnet.ru/mt685}
\transl
\jour Siberian Adv. Math.
\yr 2023
\vol 33
\issue 4
\pages 338--346
\crossref{https://doi.org/10.1134/S1055134423040065}
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  • This publication is cited in the following 3 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
    Математические труды Siberian Advances in Mathematics
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