High-Dimensional Bayesian Clustering with Variable Selection: The R Package bclust

Vahid Partovi Nia and Anthony C. Davison

Journal of Statistical Software, 2012, vol. 047, issue i05

Abstract: The R package bclust is useful for clustering high-dimensional continuous data. The package uses a parametric spike-and-slab Bayesian model to downweight the effect of noise variables and to quantify the importance of each variable in agglomerative clustering. We take advantage of the existence of closed-form marginal distributions to estimate the model hyper-parameters using empirical Bayes, thereby yielding a fully automatic method. We discuss computational problems arising in implementation of the procedure and illustrate the usefulness of the package through examples.

Date: 2012-04-18
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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:047:i05

DOI: 10.18637/jss.v047.i05

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