Model selection in nonparametric regression

Marten Wegkamp

doi:10.1214/aos/1046294464

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Home > Journals > Ann. Statist. > Volume 31 > Issue 1 > Article

Februrary 2003 Model selection in nonparametric regression

Marten Wegkamp

Ann. Statist. 31(1): 252-273 (Februrary 2003). DOI: 10.1214/aos/1046294464

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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