Model selection in nonparametric regression
The Annals of Statistics · 2003 · Volume 31 · Issue 1
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.
Keywords
60F05, 60F17, 60G15, 62E20, adaptive estimation, classification, data-splitting, Least squares estimation, Model selection, penalized least squares, VC-major classes
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