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Theory of Stochastic Processes, 2007, Volume 13(29), Issue 2, Pages 316–327 (Mi thsp208)  

On local linear estimation in nonparametric errors-in-variables models

Silvelyn  Zwanzig

Department of Mathematics, Uppsala University, SE-75106 Uppsala, Box 480 Sweden
References:
Abstract: Local linear methods are applied to a nonparametric regression model with normal errors in the variables and uniform distribution of the variables. The local neighborhood is determined with help of deconvolution kernels. Two different linear estimation method are used: the naive estimator and the total least squares estimator. Both local linear estimators are consistent. But only the local naive estimator delivers an estimation of the tangent.
Keywords: Error in variable, measurement errors, nonparametric regression, deconvolution, kernel methods, local linear regression, naive estimation, total least squares.
Bibliographic databases:
Document Type: Article
MSC: 62G08, 62G05, 62G20
Language: English
Citation: Silvelyn Zwanzig, “On local linear estimation in nonparametric errors-in-variables models”, Theory Stoch. Process., 13(29):2 (2007), 316–327
Citation in format AMSBIB
\Bibitem{Zwa07}
\by Silvelyn ~Zwanzig
\paper On local linear estimation in
nonparametric errors-in-variables
models
\jour Theory Stoch. Process.
\yr 2007
\vol 13(29)
\issue 2
\pages 316--327
\mathnet{http://mi.mathnet.ru/thsp208}
\mathscinet{https://mathscinet.ams.org/mathscinet-getitem?mr=2343833}
\zmath{https://zbmath.org/?q=an:1153.62033}
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  • https://www.mathnet.ru/eng/thsp/v13/i2/p316
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