Estimating the Variance of a Kernel Density Estimation

Bilal Nehme; Olivier Strauss; Kevin Loquin

doi:10.1007/978-3-642-14746-3_60

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Estimating the Variance of a Kernel Density Estimation

Bilal Nehme, Olivier Strauss et Kevin Loquin

Combining Soft Computing and Statistical Methods in Data Analysis, Vol.77, pp.483-490

Advances in Intelligent and Soft Computing

01/01/2010

DOI: https://doi.org/10.1007/978-3-642-14746-3_60

Résumé

Computer Science

Computer Science, Artificial Intelligence

Computer Science, Software Engineering

Computer Science, Theory & Methods

Mathematics

Physical Sciences

Science & Technology

Statistics & Probability

Technology

This article proposes an interval-valued extension of kernel density estimation. We show that the imprecision of this interval-valued estimation is highly correlated with the variance of the density estimation induced by the statistical variations of the set of observations.

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Détails

Titre: Estimating the Variance of a Kernel Density Estimation
Créateurs - sans rôle: Bilal Nehme - LIRMM, F-34095 Montpellier 5, France
Olivier Strauss - LIRMM, F-34095 Montpellier 5, France
Kevin Loquin - Ecole Natl Super Telecommun Bretagne, F-75634 Paris, France
Contributeurs - sans rôle: C Borgelt
G GonzalezRodriguez
W Trutschnig
M A Lubiano
M A Gil
P Grzegorzewski
O Hryniewicz
Détails de publication: Combining Soft Computing and Statistical Methods in Data Analysis, Vol.77, pp.483-490
Publications en série: Advances in Intelligent and Soft Computing
Éditeur: Springer Nature
Nombre de pages: 2
Note de subvention: VOODDO, a project of ANR; Agence Nationale de la Recherche (ANR) Languedoc Roussillon, France; Region Occitanie
Identifiants: 99156880709311
Unité académique: Laboratoire d'Informatique de Robotique et de Microélectronique de Mtp - LIRMM
Langue: English
Type de ressource: Conference proceeding