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 Probl. Peredachi Inf., 1999, Volume 35, Issue 2, Pages 67–74 (Mi ppi443)

Methods of Signal Processing

Nonparametric Estimation of Linear Functionals of the Regression Function for a Known Conditional Distribution of the Observation Noise

Yu. I. Pastukhova

Abstract: For the case where an observation plan is given and the distribution function of the additive noise of observations is known, we obtain a nonparametric estimate of linear functionals of the regression function. This estimate asymptotically attains the minimax bound of risks for the quadratic loss function.

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English version:
Problems of Information Transmission, 1999, 35:2, 150–157

Bibliographic databases:

UDC: 621.391.1:519.27

Citation: Yu. I. Pastukhova, “Nonparametric Estimation of Linear Functionals of the Regression Function for a Known Conditional Distribution of the Observation Noise”, Probl. Peredachi Inf., 35:2 (1999), 67–74; Problems Inform. Transmission, 35:2 (1999), 150–157

Citation in format AMSBIB
\Bibitem{Pas99} \by Yu.~I.~Pastukhova \paper Nonparametric Estimation of Linear Functionals of the Regression Function for a~Known Conditional Distribution of the Observation Noise \jour Probl. Peredachi Inf. \yr 1999 \vol 35 \issue 2 \pages 67--74 \mathnet{http://mi.mathnet.ru/ppi443} \mathscinet{http://www.ams.org/mathscinet-getitem?mr=1728908} \zmath{https://zbmath.org/?q=an:0946.62046} \transl \jour Problems Inform. Transmission \yr 1999 \vol 35 \issue 2 \pages 150--157 \crossref{https://doi.org/10.3102/0034654306298273} 

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This publication is cited in the following articles:
1. Yu. I. Pastukhova, “Asymptotically Efficient Estimation of Smooth Functionals of the Regression Function for a Known Distribution of the Observation Noise”, Problems Inform. Transmission, 40:4 (2004), 365–378
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