Title :

Regression estimation by local polynomial fitting for multivariate data streams

Author(s) :

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

Journal title :

Statistical Papers

Pages :

813–843

Publisher :

Springer Verlag

Publication date :

2016-06-24

ISSN :

0932-5026

English keyword(s) :

Stochastic approximation
Data streams
Weakly dependent sequences
Kernel methods
Local polynomial

HAL domain(s) :

Sciences de l'Homme et Société/Méthodes et statistiques

English abstract : [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 ...
Show more >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.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Lille Économie Management (LEM) - UMR 9221

Source :

Harvested from HAL