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Adaptive nonparametric estimation in heteroscedastic regression models. Part 2: Asymptotic efficiency

Abstract

The paper deals with asymptotic properties of the adaptive procedure proposed in the author paper (2007) for estimation of unknown nonparametric regression. We prove that this procedure is asymptotically efficient for a quadratic risk. It means that the asymptotic quadratic risk for this procedure coincides with a sharp lower bound.

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