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arXiv · 1002.1538

Sharp non-asymptotic oracle inequalities for nonparametric heteroscedastic regression models

Leonid Galtchouk·Serguei Pergamenchtchikov
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Abstract

An adaptive nonparametric estimation procedure is constructed for heteroscedastic regression when the noise variance depends on the unknown regression. A non-asymptotic upper bound for a quadratic risk (oracle inequality) is obtained

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Leonid Galtchouk, Serguei Pergamenchtchikov. 2010-02-08. Sharp non-asymptotic oracle inequalities for nonparametric heteroscedastic regression models. https://arxiv.org/abs/1002.1538

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