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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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Main Authors: TATARINOVA, TATIANA, BOUCK, JOHN, SCHUMITZKY, ALAN
格式: Artigo
語言:Inglês
出版: 2008
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在線閱讀:https://ncbi.nlm.nih.gov/pmc/articles/PMC2696055/
https://ncbi.nlm.nih.gov/pubmed/18763739
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