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Februrary 2003 Model selection in nonparametric regression
Marten Wegkamp
Ann. Statist. 31(1): 252-273 (Februrary 2003). DOI: 10.1214/aos/1046294464

Abstract

Model selection using a penalized data-splitting device is studied in the context of nonparametric regression. Finite sample bounds under mild conditions are obtained. The resulting estimates are adaptive for large classes of functions.

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Marten Wegkamp. "Model selection in nonparametric regression." Ann. Statist. 31 (1) 252 - 273, Februrary 2003. https://doi.org/10.1214/aos/1046294464

Information

Published: Februrary 2003
First available in Project Euclid: 26 February 2003

zbMATH: 1019.62037
MathSciNet: MR1962506
Digital Object Identifier: 10.1214/aos/1046294464

Subjects:
Primary: 60F05 , 60F17
Secondary: 60G15 , 62E20

Keywords: adaptive estimation , ‎classification‎ , data-splitting , Least squares estimation , Model selection , penalized least squares , VC-major classes

Rights: Copyright © 2003 Institute of Mathematical Statistics

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Vol.31 • No. 1 • Februrary 2003
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