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Sharp non-asymptotic oracle inequalities for non-parametric heteroscedastic regression models. (English) Zbl 1154.62329

Summary: 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.

MSC:

62G08 Nonparametric regression and quantile regression
62G20 Asymptotic properties of nonparametric inference
62G05 Nonparametric estimation
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