Treffer: A Recursive Algorithm for Mixture of Densities Estimation
Title:
A Recursive Algorithm for Mixture of Densities Estimation
Authors:
Source:
IEEE transactions on information theory. 59(10):6893-6906
Publisher Information:
New York, NY: Institute of Electrical and Electronics Engineers, 2013.
Publication Year:
2013
Physical Description:
print, 33 ref
Original Material:
INIST-CNRS
Subject Terms:
Telecommunications, Télécommunications, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Théorie de l'information, Information theory, Algorithme récursif, Recursive algorithm, Algoritmo recursivo, Espace Hilbert, Hilbert space, Espacio Hilbert, Estimation densité, Density estimation, Estimación densidad, Estimation récursive, Recursive estimation, Fonction caractéristique, Characteristic function, Función característica, Localisation, Localization, Localización, Méthode itérative, Iterative method, Método iterativo, Simulation, Simulación, Boosting, copula, elliptic distribution, empirical characteristic function, location model, recursive algorithm
Document Type:
Fachzeitschrift
Article
File Description:
text
Language:
English
Author Affiliations:
Department of Economics, Royal Holloway, Egham Hill, Egham TW20 OEX, United Kingdom
ISSN:
0018-9448
Rights:
Copyright 2014 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Telecommunications and information theory
Accession Number:
edscal.27783708
Database:
PASCAL Archive
Weitere Informationen
Recursive algorithms for the estimation of mixtures of densities have attracted a lot of attention in the last 10 years. Here an algorithm for recursive estimation is studied. It complements existing approaches in the literature, as it is based on conditions that are usually very weak. For example, the parameter space over which the mixture is taken does not need to be necessarily bounded. The essence of the procedure is to combine density estimation via empirical characteristic function together with an iterative Hilbert space approximation algorithm. The conditions for consistency of the estimator are verified for three important statistical problems. A simulation study is also included.