Nonparametric density and regression estimation for functional data

Abstract

We consider kernel estimation of density and regression based on functional data. We prove the strong convergence and the asymptotic normality of the centered estimators. We include results both for independent and mixing data, as the mathematical treatment and conditions for convergence are different.