bclust: Bayesian clustering using spike-and-slab hierarchical model,
suitable for clustering high-dimensional data
The package builds a dendrogram with log posterior as a
natural distance defined by the model. It is also capable to
computing Bayesian discrimination probabilities equivalent to
the implemented Bayesian clustering. Spike-and-Slab models are
adopted in a way to be able to produce an importance measure
for clustering and discriminant variables. The method works
properly for data with small sample size and high dimensions.
The model parameter estimation maybe difficult, depending on
data structure and the chosen distribution family.