Robust adaptive efficient estimation for semi-Markov nonparametric regression models
Statistics Theory
2017-03-28 v2 Statistics Theory
Abstract
We consider the nonparametric robust estimation problem for regression models in continuous time with semi-Markov noises. An adaptive model selection procedure is proposed. Under general moment conditions on the noise distribution a sharp non-asymptotic oracle inequality for the robust risks is obtained and the robust efficiency is shown. It turns out that for semi-Markov models the robust minimax convergence rate may be faster or slower than the classical one.
Cite
@article{arxiv.1604.04516,
title = {Robust adaptive efficient estimation for semi-Markov nonparametric regression models},
author = {Vlad Barbu and Slim Beltaif and Serguei Pergamenchtchikov},
journal= {arXiv preprint arXiv:1604.04516},
year = {2017}
}