High-dimensional Bayesian clustering with variable selection: the R package bclust

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.