Asymptotic normality of recursive estimators under strong mixing conditions
Statistics Theory
2012-12-11 v2 Statistics Theory
Abstract
The main purpose of this paper is to estimate the regression function by using a recursive nonparametric kernel approach. We derive the asymptotic normality for a general class of recursive kernel estimate of the regression function, under strong mixing conditions. Our purpose is to extend the work of Roussas and Tran [17] concerning the Devroye-Wagner estimate.
Keywords
Cite
@article{arxiv.1211.5767,
title = {Asymptotic normality of recursive estimators under strong mixing conditions},
author = {Aboubacar Amiri},
journal= {arXiv preprint arXiv:1211.5767},
year = {2012}
}