Abstract
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.