Adaptive estimation for spatially varying coefficient models

Abstract

In this paper, a new adaptive estimation approach is proposed for the spatially varying coefficient models with unknown error distribution, unlike geographically weighted regression (GWR) and local linear geographically weighted regression (LL), this method can adapt to different error distributions. A generalized Modal EM algorithm is presented to implement the estimation, and the asymptotic property of the estimator is established. Simulation and real data results show that the gain of the new adaptive method over the GWR and LL estimation is considerable for the error of non-Gaussian distributions.