The fundamental problem of gibbs sampler in mixture models
Journal Title: Scientific Journal of Pure and Applied Sciences - Year 2014, Vol 3, Issue 8
Abstract
The mixture models were rstly studied by Pearson in 1894. These models are strong tools,through which the complicated systems can be analyzed in a wide range of disciplines such as As-tronomy, Economics, Mechanics, etc. although the structure of these models is apparently simple,it is very complicated to obtain maximum likelihood estimators and Bayesian ones in particular andit needs to be approximated in most cases. In this paper, we apply the Gibbs Sampling in order toapproximate the Bayesian Estimator in Mixture models, present the Gibbs algorithms for the familyof exponential distributions and nally, we would show the disadvantage of this algorithm throughan example.
Authors and Affiliations
G. H. Gholami*| Department of Mathematics, Faculty of science, Urmia University, Urmia, IRAN., A. Etemadi| Department of Mathematics, Urmia Branch, Islamic Azad University, Urmia, IRAN., H. Rasi| Department of Statistics, Faculty of Mathematics, Tabriz University, Tabriz, IRAN.
Keywords
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- EP ID EP407
- DOI 10.14196/sjpas.v3i8.1516
- Views 463
- Downloads 18
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