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.

Mots clés

agglomerative clustering, Bayesian clustering, Bayesian variable selection, dendro- gram, hierarchical clustering, R, spike-and-slab model.