Non-parametric level set estimation for ...
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
Non-parametric level set estimation for spatial data
Author(s) :
Dabo-Niang, Sophie [Auteur]
MOdel for Data Analysis and Learning [MODAL]
Lille économie management - UMR 9221 [LEM]
Nkiet, Guy-Martial [Auteur]
Ecole polytechnique de Masuku [EPM]
Bouka, Stéphane [Auteur]
Faculté des Sciences [Université des Sciences et Techniques de Masuku]
MOdel for Data Analysis and Learning [MODAL]
Lille économie management - UMR 9221 [LEM]
Nkiet, Guy-Martial [Auteur]
Ecole polytechnique de Masuku [EPM]
Bouka, Stéphane [Auteur]
Faculté des Sciences [Université des Sciences et Techniques de Masuku]
Journal title :
Advances and Applications in Statistics
Pages :
119 - 158
Publisher :
Pushpa Publishing House
Publication date :
2015-09-12
ISSN :
0972-3617
HAL domain(s) :
Mathématiques [math]/Statistiques [math.ST]
English abstract : [en]
A non-parametric level set estimator of the density of a stationary d-dimensional spatial process is proposed. The estimator is deduced from a non-parametric kernel density estimator. Berry-Esseen bounds are established ...
Show more >A non-parametric level set estimator of the density of a stationary d-dimensional spatial process is proposed. The estimator is deduced from a non-parametric kernel density estimator. Berry-Esseen bounds are established and used to give consistency results of the kernel level set estimation, derived from that of the kernel density estimate under some mild conditions.Show less >
Show more >A non-parametric level set estimator of the density of a stationary d-dimensional spatial process is proposed. The estimator is deduced from a non-parametric kernel density estimator. Berry-Esseen bounds are established and used to give consistency results of the kernel level set estimation, derived from that of the kernel density estimate under some mild conditions.Show less >
Language :
Anglais
Popular science :
Non
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