Nonparametric kernel estimation of the probability density function of regression errors using estimated residuals
Statistics Theory
2010-10-05 v1 Statistics Theory
Abstract
This paper deals with the nonparametric density estimation of the regression error term assuming its independence with the covariate. The difference between the feasible estimator which uses the estimated residuals and the unfeasible one using the true residuals is studied. An optimal choice of the bandwidth used to estimate the residuals is given. We also study the asymptotic normality of the feasible kernel estimator and its rate-optimality.
Cite
@article{arxiv.1010.0439,
title = {Nonparametric kernel estimation of the probability density function of regression errors using estimated residuals},
author = {Rawane Samb},
journal= {arXiv preprint arXiv:1010.0439},
year = {2010}
}