We study asymptotic properties of M-estimates of regression parameters in linear models in which errors are dependent. Weak and strong Bahadur representations of the M-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.
"M-estimation of linear models with dependent errors." Ann. Statist. 35 (2) 495 - 521, April 2007. https://doi.org/10.1214/009053606000001406