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An approach to constructing explicit estimators in nonlinear regression Full article

Journal Siberian Advances in Mathematics
ISSN: 1055-1344 , E-ISSN: 1934-8126
Output data Year: 2023, Volume: 33, Number: 4, Pages: 338-346 Pages count : 9 DOI: 10.1134/S1055134423040065
Tags nonlinear regression, nonparametric regression, kernel estimators, uniform consistency, fixed regressors, random regressors
Authors Linke Yu.Yu. 1 , Borisov I.S. 1
Affiliations
1 Sobolev Institute of Mathematics

Funding (1)

1 Sobolev Institute of Mathematics FWNF-2022-0015

Abstract: We consider the problem of constructing explicit consistent estimators of finitedimensional parameters of nonlinear regression models using various nonparametric kernel estimators.
Cite: Linke Y.Y. , Borisov I.S.
An approach to constructing explicit estimators in nonlinear regression
Siberian Advances in Mathematics. 2023. V.33. N4. P.338-346. DOI: 10.1134/S1055134423040065 Scopus РИНЦ OpenAlex
Original: Линке Ю.Ю. , Борисов И.С.
Об одном подходе к построению явных оценок в задачах нелинейной регрессии
Математические труды. 2023. Т.26. №2. С.177-191. DOI: 10.33048/mattrudy.2023.26.209 РИНЦ
Dates:
Submitted: Jun 25, 2023
Accepted: Jul 20, 2023
Published print: Dec 14, 2023
Published online: Dec 14, 2023
Identifiers:
Scopus: 2-s2.0-85179666799
Elibrary: 65433164
OpenAlex: W4389735967
Citing:
DB Citing
OpenAlex 4
Scopus 3
Elibrary 3
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