Linear trimmed means for the linear regression with AR(1) errors model

Abstract

For the linear regression with AR(1) errors model, the robust generalized and feasible generalized estimators of Lai et al. (2003) of regression parameters are shown to have the desired property of a robust Gauss Markov theorem. This is done by showing that these two estimators are the best among classes of linear trimmed means. Monte Carlo and data analysis for this technique have been performed. (C) 2010 Elsevier B.V. All rights reserved.