Estimating the error distribution function in nonparametric regression
Statistics Theory
2018-10-26 v2 Statistics Theory
Abstract
We construct an efficient estimator for the error distribution function of the nonparametric regression model Y = r(Z) + e. Our estimator is a kernel smoothed empirical distribution function based on residuals from an under-smoothed local quadratic smoother for the regression function.
Cite
@article{arxiv.1810.01645,
title = {Estimating the error distribution function in nonparametric regression},
author = {Ursula U. Müller and Anton Schick and Wolfgang Wefelmeyer},
journal= {arXiv preprint arXiv:1810.01645},
year = {2018}
}
Comments
Unpublished manuscript (2004), 20 pages