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.

• Publication year

  2012

• Venue

  Journal of Statistical Software

• Publication date

  2012-04-18

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.18637/JSS.V047.I05
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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