DPCD - Dirichlet Process Clustering with Dissimilarities
A Bayesian hierarchical model for clustering dissimilarity
data using the Dirichlet process. The latent configuration of
objects and the number of clusters are automatically inferred
during the fitting process. The package supports multiple
models which are available to detect clusters of various shapes
and sizes using different covariance structures. Additional
functions are included to ensure adequate model fits through
prior and posterior predictive checks.
