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ABSTRACT
This article presents the non-parametric functional estimation methods. These parametric model present, in general, a parameter of interest in the infinite dimension; most often this parameter is a function that one tries to estimate. It particularly focuses on the density by projection , distribution function and spectral density methods. These methods are of great interest being resistant to changes in models. They also allow for assisting statisticians in choosing a parametric model and are very efficient for forecasting. This presentation is illustrated by several applications.
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Denis BOSQ: Professor Emeritus, Pierre-et-Marie-Curie University, Paris 6
INTRODUCTION
In this article, we present the main non-parametric functional estimation methods. These methods have the advantage of being robust: they withstand model changes well; they can also guide the statistician in the choice of a parametric model; and they are very effective for forecasting. In particular, we study the estimation of the distribution function, density, regression and spectral density. Some applications are given in the text.
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