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Avtomatika i Telemekhanika, 2007, Issue 4, Pages 79–91 (Mi at971)  
This article is cited in 1 scientific paper (total in 1 paper)

Adaptive and Robust Systems

The iteration method of data censoring in the regression estimation problem

E. S. Kirik

Institute of Computational Modeling, Siberian Branch, Russian Academy of Sciences, Krasnoyarsk, Russia
Full-text PDF (345 kB) Citations (1)
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Abstract: A robust analog of the Nadaraya–Watson regression estimate is considered. A solution is obtained in the class of censor algorithms. A criterion and iteration procedure for determining a censored sample are proposed. The criterion is based on the analysis of residuals (errors) of estimation.
Presented by the member of Editorial Board: V. A. Lototskii

Received: 06.08.2004
English version:
Automation and Remote Control, 2007, Volume 68, Issue 4, Pages 645–656
DOI: https://doi.org/10.1134/S000511790704008X
Bibliographic databases:
Document Type: Article
PACS: 89.20.Ff
Language: Russian
Citation: E. S. Kirik, “The iteration method of data censoring in the regression estimation problem”, Avtomat. i Telemekh., 2007, no. 4, 79–91; Autom. Remote Control, 68:4 (2007), 645–656
Citation in format AMSBIB
\Bibitem{Kir07}
\by E.~S.~Kirik
\paper The iteration method of data censoring in the regression estimation problem
\jour Avtomat. i Telemekh.
\yr 2007
\issue 4
\pages 79--91
\mathnet{http://mi.mathnet.ru/at971}
\mathscinet{http://mathscinet.ams.org/mathscinet-getitem?mr=2321062}
\zmath{https://zbmath.org/?q=an:1127.62037}
\transl
\jour Autom. Remote Control
\yr 2007
\vol 68
\issue 4
\pages 645--656
\crossref{https://doi.org/10.1134/S000511790704008X}
\scopus{https://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-34247369369}
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  • https://www.mathnet.ru/eng/at/y2007/i4/p79
    • This publication is cited in the following 1 articles:
    Citing articles in Google Scholar: Russian citations, English citations
    Related articles in Google Scholar: Russian articles, English articles
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    Full-text PDF :72
    References:33
    First page:1
     
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