On robust nonparametric regression estimation for a functional regressor

We study a family of robust nonparametric estimators for a regression function based on a kernel method when the regressors are functional random variables. We establish the almost complete convergence rate of these estimators under the probability measure’s concentration property on small balls of the functional variable. Simulations are given to show our estimator’s behavior and the prediction quality for functional data.