Asymptotic normality of kernel estimates ...
Document type :
Pré-publication ou Document de travail
Title :
Asymptotic normality of kernel estimates in a regression model for random fields
Author(s) :
El Machkouri, Mohamed [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Stoica, Radu [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
Stoica, Radu [Auteur]
Laboratoire Paul Painlevé - UMR 8524 [LPP]
English keyword(s) :
Nonparametric regression estimation
asymptotic normality
kernel estimator
strongly mixing random field
asymptotic normality
kernel estimator
strongly mixing random field
HAL domain(s) :
Mathématiques [math]/Statistiques [math.ST]
Statistiques [stat]/Théorie [stat.TH]
Statistiques [stat]/Théorie [stat.TH]
English abstract : [en]
We establish the asymptotic normality of the regression estimator in a fixed-design setting when the errors are given by a field of dependent random variables. The result applies to martingale-difference or strongly mixing ...
Show more >We establish the asymptotic normality of the regression estimator in a fixed-design setting when the errors are given by a field of dependent random variables. The result applies to martingale-difference or strongly mixing random fields. On this basis, a statistical test that can be applied to image analysis is also presented.Show less >
Show more >We establish the asymptotic normality of the regression estimator in a fixed-design setting when the errors are given by a field of dependent random variables. The result applies to martingale-difference or strongly mixing random fields. On this basis, a statistical test that can be applied to image analysis is also presented.Show less >
Language :
Anglais
Comment :
20 pages
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