Local linear M-estimation for spatial processes in fixed-design models

Abstract

We investigate the local linear M-estimation for regression in a fixed-design model when the errors are from a strongly mixing random field. We establish the weak and strong consistency as well as the asymptotic normality of the local linear M-estimator. The conditions on ρ(·) used in this paper are mild and allow many important special cases such as the least square estimator and the least absolute distance estimator.