Robust Nonparametric Estimation for Functional Spatial Regression

This contribution deals with robust nonparametric regression analysis when the regressors are functional random fields. More precisely, we propose a family of robust nonparametric estimators for nonparametric functional spatial regression based on the kernel method. The main results of this work are the establishment of the almost complete convergence rate of these estimators.