Non-parametric recursive density estimation ...
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
Non-parametric recursive density estimation for spatial data
Author(s) :
Amiri, Aboubacar [Auteur]
Lille économie management - UMR 9221 [LEM]
Dabo-Niang, Sophie [Auteur]
Lille économie management - UMR 9221 [LEM]
MOdel for Data Analysis and Learning [MODAL]
Yahaya, Mohamed [Auteur]
Université des Comores
Lille économie management - UMR 9221 [LEM]
Lille économie management - UMR 9221 [LEM]
Dabo-Niang, Sophie [Auteur]
Lille économie management - UMR 9221 [LEM]
MOdel for Data Analysis and Learning [MODAL]
Yahaya, Mohamed [Auteur]
Université des Comores
Lille économie management - UMR 9221 [LEM]
Journal title :
Comptes Rendus. Mathématique
Publisher :
Académie des sciences (Paris)
Publication date :
2016
ISSN :
1631-073X
HAL domain(s) :
Mathématiques [math]/Statistiques [math.ST]
English abstract : [en]
This paper deals with non-parametric density estimation for spatial data. We study the asymptotic properties of a new recursive version of the Parzen–Rozenblatt estimator. The mean square error and an almost sure convergence ...
Show more >This paper deals with non-parametric density estimation for spatial data. We study the asymptotic properties of a new recursive version of the Parzen–Rozenblatt estimator. The mean square error and an almost sure convergence result with rate of such estimator are derived.Show less >
Show more >This paper deals with non-parametric density estimation for spatial data. We study the asymptotic properties of a new recursive version of the Parzen–Rozenblatt estimator. The mean square error and an almost sure convergence result with rate of such estimator are derived.Show less >
Language :
Anglais
Popular science :
Non
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