Treffer: Bayesian analysis of finite mixtures of multinomial and negative-multinomial distributions

Title:
Bayesian analysis of finite mixtures of multinomial and negative-multinomial distributions
Authors:
RUFO, M. J, PEREZ, C. J, MARTIN, J
Source:
Advances in mixture modelsComputational statistics & data analysis. 51(11):5452-5466
Publisher Information:
Amsterdam: Elsevier Science, 2007.
Publication Year:
2007
Physical Description:
print, 3/4 p
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, Théorie des probabilités et processus stochastiques, Probability theory and stochastic processes, Lois de probabilités, Distribution theory, Statistiques, Statistics, Généralités, General topics, Analyse multivariable, Multivariate analysis, Analyse numérique. Calcul scientifique, Numerical analysis. Scientific computation, Analyse numérique, Numerical analysis, Probabilités et statistiques numériques, Numerical methods in probability and statistics, Algorithme, Algorithm, Algoritmo, Analyse donnée, Data analysis, Análisis datos, Approximation, Aproximación, Calcul statistique, Statistical computation, Cálculo estadístico, Chaîne Markov, Markov chain, Cadena Markov, Estimation Bayes, Bayes estimation, Estimación Bayes, Fonction répartition, Distribution function, Función distribución, Implémentation, Implementation, Implementación, Loi multinomiale, Multinomial distribution, Ley multinomial, Mélange loi probabilité, Mixed distribution, Mezcla ley probabilidad, Méthode Monte Carlo, Monte Carlo method, Método Monte Carlo, 60E05, 60J10, 62E17, 65C05, 65C40, Analyse bayésienne, Bayesian inference, Finite mixture, Gibbs sampling, Label-switching, Negative-multinomial distribution
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Mathematics, Escuela Politécnica, University of Extremadura, Avda. de la Universidad s/n, 10071 Cdceres, Spain
ISSN:
0167-9473
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=18830905
Rights:
Copyright 2007 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.18830905
Database:
PASCAL Archive

Weitere Informationen

The Bayesian implementation of finite mixtures of distributions has been an area of considerable interest within the literature. Computational advances on approximation techniques such as Markov chain Monte Carlo (MCMC) methods have been a keystone to Bayesian analysis of mixture models. This paper deals with the Bayesian analysis of finite mixtures of two particular types of multidimensional distributions: the multinomial and the negative-multinomial ones. A unified framework addressing the main topics in a Bayesian analysis is developed for the case with a known number of component distributions. In particular, theoretical results and algorithms to solve the label-switching problem are provided. An illustrative example is presented to show that the proposed techniques are easily applied in practice.