Model selection in nonparametric regression

Marten Wegkamp

doi:10.1214/aos/1046294464

2003-02-01

Marten Wegkamp

DOI：10.1214/aos/1046294464

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摘要

En 中文

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.

Keyword:

adaptive estimation

classification

data-splitting

least squares estimation

model selection

penalized least squares

VC-major classes

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期刊

Annals of Statistics

IF:

3.7

论文数:

2.8K

被引数:

2.9W

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