M-estimation of linear models with dependent errors
Statistics Theory
2009-09-29 v3 Probability
Statistics Theory
Abstract
We study asymptotic properties of -estimates of regression parameters in linear models in which errors are dependent. Weak and strong Bahadur representations of the -estimates are derived and a central limit theorem is established. The results are applied to linear models with errors being short-range dependent linear processes, heavy-tailed linear processes and some widely used nonlinear time series.
Cite
@article{arxiv.math/0412268,
title = {M-estimation of linear models with dependent errors},
author = {Wei Biao Wu},
journal= {arXiv preprint arXiv:math/0412268},
year = {2009}
}
Comments
Published at http://dx.doi.org/10.1214/009053606000001406 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)