Asymptotic properties of one-step weighted $M$-estimators and applications to some regression problems
Statistics Theory
2015-07-07 v2 Statistics Theory
Abstract
We study asymptotic behavior of one-step weighted -estimators based on samples from arrays of not necessarily identically distributed random variables and representing explicit approximations to the corresponding consistent weighted -estimators. Sufficient conditions are presented for asymptotic normality of the one-step weighted -estimators under consideration. As a consequence, we consider some well-known nonlinear regression models where the procedure mentioned allow us to construct explicit asymptotically optimal estimators.
Keywords
Cite
@article{arxiv.1505.02725,
title = {Asymptotic properties of one-step weighted $M$-estimators and applications to some regression problems},
author = {Yu. Yu. Linke},
journal= {arXiv preprint arXiv:1505.02725},
year = {2015}
}
Comments
in Russian. arXiv admin note: substantial text overlap with arXiv:1503.03393