mloss.org Nonparametric Sparse Factor Analysishttp://mloss.orgUpdates and additions to Nonparametric Sparse Factor AnalysisenFri, 26 Jul 2013 01:02:02 -0000Nonparametric Sparse Factor Analysis 1http://mloss.org/software/view/476/<html><p>This is the core MCMC sampler for the nonparametric sparse factor analysis model presented in
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<p>David A. Knowles and Zoubin Ghahramani (2011). Nonparametric Bayesian Sparse Factor Models with application to Gene Expression modelling. Annals of Applied Statistics
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<p>From the abstract:
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<p>A nonparametric Bayesian extension of Factor Analysis (FA) is proposed where observed data Y is modeled as a linear superposition, G, of a potentially infinite number of hidden factors, X. The Indian Buffet Process (IBP) is used as a prior on G to incorporate sparsity and to allow the number of latent features to be inferred. The model's utility for modeling gene expression data is investigated using randomly generated datasets based on a known sparse connectivity matrix for E. Coli, and on three biological datasets of increasing complexity.
</p></html>David A. Knowles, Zoubin GhahramaniFri, 26 Jul 2013 01:02:02 -0000http://mloss.org/software/rss/comments/476http://mloss.org/software/view/476/nonparametric bayesfactor analysis