Result: Robustness via a mixture of exponential power distributions
Title:
Robustness via a mixture of exponential power distributions
Authors:
Source:
Computational statistics & data analysis. 42(1-2):111-121
Publisher Information:
Amsterdam: Elsevier Science, 2003.
Publication Year:
2003
Physical Description:
print, 15 ref
Original Material:
INIST-CNRS
Subject Terms:
Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Probabilités et statistiques, Probability and statistics, Statistiques, Statistics, Inférence paramétrique, Parametric inference, Applications, Assurances, économie, finance, Insurance, economics, finance, Donnée financière, Financial data, Datos financieros, Echantillonnage Gibbs, Gibbs sampling, Muestreo Gibbs, Estimation paramètre, Parameter estimation, Estimación parámetro, Etude théorique, Theoretical study, Estudio teórico, Loi a priori, Prior distribution, Ley a priori, Mélange loi probabilité, Mixed distribution, Mezcla ley probabilidad, Méthode statistique, Statistical method, Método estadístico, Robustesse estimateur, Estimator robustness, Robustez estimador, Simulation numérique, Numerical simulation, Simulación numérica, Algorithme échantillonnage, Sampling algorithm, Loi puissance exponentielle, Exponential power distribution, Rejet adaptatif, Adaptive rejection
Document Type:
Academic journal
Article
File Description:
text
Language:
English
Author Affiliations:
Department of Statistics. University of Haifa, Mount Carmel, Haifa 31905, Israel
ISSN:
0167-9473
Rights:
Copyright 2003 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:
Mathematics
Accession Number:
edscal.14643508
Database:
PASCAL Archive
Further Information
A mixture of exponential power distributions (EPD) is suggested and is shown to possess robust qualities. The Gibbs sampler is applied for estimating the unknown parameters of the model and its algorithm is devised in order to allow a wide range of prior distributions for the unknown parameters. Numerical studies, using real financial data, demonstrate the effectiveness of the proposed model and a theoretical study explains the superiority of the EPD mixture over a normal mixture.