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Heteroscedastic normal-exponential mixture models: Bayesian and classical approaches
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DOI：10.1016/j.amc.2011.09.005.png)
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In this paper, we introduce a Bayesian analysis for mixture of distributions belonging to the exponential family. As a special case we consider a mixture of normal exponential distributions including joint modeling of the mean and variance. We also consider joint modeling of the mean and variance heterogeneity. Markov Chain Monte Carlo (MCMC) methods are used to obtain the posterior summaries of interest. We also introduce and apply an EM algorithm, where the maximization is obtained applying the Fisher scoring algorithm. Finally, we also include analysis of real data sets to illustrate the proposed methodology. (C) 2011 Elsevier Inc. All rights reserved.
Keyword:
Mixture models
Variance heterogeneity
Bayesian methods
MCMC simulation
Classical approach
EM algorithm
Fisher scoring algorithm
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