منابع مشابه
A Simple Solution to Bayesian Mixture Labeling
The label switching problem is one of the fundamental problems in Bayesian mixture analysis. Using all the Markov chain Monte Carlo samples as the initials for the EM algorithm, we propose to label the samples based on the modes they converge to. Our method is based on the assumption that the samples converged to the same mode have the same labels. If a relative noninformative prior is used or ...
متن کاملBayesian Regularization for Normal Mixture Estimation and Model-Based Clustering
Normal mixture models are widely used for statistical modeling of data, including cluster analysis. However maximum likelihood estimation (MLE) for normal mixtures using the EM algorithm may fail as the result of singularities or degeneracies. To avoid this, we propose replacing the MLE by a maximum a posteriori (MAP) estimator, also found by the EM algorithm. For choosing the number of compone...
متن کاملNonparametric Bayesian Clustering via Infinite Warped Mixture Models
We introduce a flexible class of mixture models for clustering and density estimation. Our model allows clustering of non-linearly-separable data, produces a potentially low-dimensional latent representation, automatically infers the number of clusters, and produces a density estimate. Our approach makes use of two tools from Bayesian nonparametrics: a Dirichlet process mixture model to allow a...
متن کاملBayesian mixture model based clustering of replicated microarray data
MOTIVATION Identifying patterns of co-expression in microarray data by cluster analysis has been a productive approach to uncovering molecular mechanisms underlying biological processes under investigation. Using experimental replicates can generally improve the precision of the cluster analysis by reducing the experimental variability of measurements. In such situations, Bayesian mixtures allo...
متن کاملBayesian infinite mixture model based clustering of gene expression profiles
MOTIVATION The biologic significance of results obtained through cluster analyses of gene expression data generated in microarray experiments have been demonstrated in many studies. In this article we focus on the development of a clustering procedure based on the concept of Bayesian model-averaging and a precise statistical model of expression data. RESULTS We developed a clustering procedur...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Communications in Statistics - Theory and Methods
سال: 2012
ISSN: 0361-0926,1532-415X
DOI: 10.1080/03610926.2010.526741