Adaptive nonparametric estimation in heteroscedastic regression models. Part 2: Asymptotic efficiency
Statistics Theory
2008-12-18 v1 Statistics Theory
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.
Cite
@article{arxiv.0804.1584,
title = {Adaptive nonparametric estimation in heteroscedastic regression models. Part 2: Asymptotic efficiency},
author = {Leonid Galtchouk and Serguey Pergamenshchikov},
journal= {arXiv preprint arXiv:0804.1584},
year = {2008}
}