Recursive estimation of nonparametric regression with functional covariate
Statistics Theory
2013-08-07 v2 Statistics Theory
Abstract
The main purpose is to estimate the regression function of a real random variable with functional explanatory variable by using a recursive nonparametric kernel approach. The mean square error and the almost sure convergence of a family of recursive kernel estimates of the regression function are derived. These results are established with rates and precise evaluation of the constant terms. Also, a central limit theorem for this class of estimators is established. The method is evaluated on simulations and real data set studies.
Cite
@article{arxiv.1211.2780,
title = {Recursive estimation of nonparametric regression with functional covariate},
author = {Aboubacar Amiri and Christophe Crambes and Baba Thiam},
journal= {arXiv preprint arXiv:1211.2780},
year = {2013}
}
Comments
32 pages, 4 figures