Efficient estimation of the error distribution function in heteroskedastic nonparametric regression with missing data
Methodology
2016-10-28 v1
Abstract
A residual-based empirical distribution function is proposed to estimate the distribution function of the errors of a heteroskedastic nonparametric regression with responses missing at random based on completely observed data, and this estimator is shown to be asymptotically most precise.
Cite
@article{arxiv.1610.08768,
title = {Efficient estimation of the error distribution function in heteroskedastic nonparametric regression with missing data},
author = {Justin Chown},
journal= {arXiv preprint arXiv:1610.08768},
year = {2016}
}
Comments
Preprint is 20 pages in length