Wavelet-based estimation in a semiparametric regression model
Statistics Theory
2020-05-04 v2 Statistics Theory
Abstract
In this paper, we introduce a wavelet-based method for estimating the EDR space in Li's semiparametric regression model for achieving dimension reduction. This method is obtained by using linear wavelet estimators of the density and regression functions that are involved in the covariance matrix of conditional expectation whose spectral analysis gives the EDR directions. Then, consistency of the proposed estimators is proved. A simulation study that allow one to evaluate the performance of the proposal with comparison to existing methods is presented.
Cite
@article{arxiv.2004.14502,
title = {Wavelet-based estimation in a semiparametric regression model},
author = {Emmanuel de Dieu Nkou and Guy Martial Nkiet},
journal= {arXiv preprint arXiv:2004.14502},
year = {2020}
}