Modelization local linear regression for Functional random variables.
Local linear methods have been shown to dominate local constant methods for the nonparametric estimation of regression functions.In this paper we study the nonparametric regression of a scalar response on a functional variable (i.e. one observation can be a curve, surface, or any other object lying into an infinite-dimensional space)We provide the asymptotic mean square error under some general conditions .The main results of this functional local method is to propose an explicit expression of a kernel-type estimator which makes its fast while keeping good predictive performance.
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