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KULLBACK-LEIBLER MARKOV CHAIN MONTE CARLO — A NEW ALGORITHM FOR FINITE MIXTURE ANALYSIS AND ITS APPLICATION TO GENE EXPRESSION DATA

In this paper, we study Bayesian analysis of nonlinear hierarchical mixture models with a finite but unknown number of components. Our approach is based on Markov chain Monte Carlo (MCMC) methods. One of the applications of our method is directed to the clustering problem in gene expression analysis...

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Bibliographic Details
Main Authors: TATARINOVA, TATIANA, BOUCK, JOHN, SCHUMITZKY, ALAN
Format: Artigo
Language:Inglês
Published: 2008
Subjects:
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC2696055/
https://ncbi.nlm.nih.gov/pubmed/18763739
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