Overview
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.
Read this article from a comprehensive knowledge base, updated and supplemented with articles reviewed by scientific committees.
Read the articleAUTHOR
-
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.
Exclusive to subscribers. 97% yet to be discovered!
Already subscribed? Log in!
Functional estimation
The different models
Article included in this offer
"Mathematics"
(
167 articles
)
Updated and enriched with articles validated by our scientific committees
A set of exclusive tools to complement the resources
Bibliography
Exclusive to subscribers. 97% yet to be discovered!
Already subscribed? Log in!
