Titre :

Regression estimation by local polynomial fitting for multivariate data streams

Auteur(s) :

Amiri, Aboubacar [Auteur]
Lille économie management - UMR 9221 [LEM]
Thiam, Baba [Auteur]
Lille économie management - UMR 9221 [LEM]

Titre de la revue :

Statistical Papers

Pagination :

813–843

Éditeur :

Springer Verlag

Date de publication :

2016-06-24

ISSN :

0932-5026

Mot(s)-clé(s) en anglais :

Stochastic approximation
Data streams
Weakly dependent sequences
Kernel methods
Local polynomial

Discipline(s) HAL :

Sciences de l'Homme et Société/Méthodes et statistiques

Résumé en anglais : [en]

In this paper we study a local polynomial estimator of the regression function and its derivatives. We propose a sequential technique based on a multivariate counterpart of the stochastic approximation method for successive ...
Lire la suite >In this paper we study a local polynomial estimator of the regression function and its derivatives. We propose a sequential technique based on a multivariate counterpart of the stochastic approximation method for successive experiments for the local polynomial estimation problem. We present our results in a more general context by considering the weakly dependent sequence of stream data, for which we provide an asymptotic bias-variance decomposition of the considered estimator. Additionally, we study the asymptotic normality of the estimator and we provide algorithms for the practical use of the method in data streams framework.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :

• Lille Économie Management (LEM) - UMR 9221

Source :

Harvested from HAL