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dpmixsim: Dirichlet Process Mixture model simulation for clustering and image segmentation

The package implements a Dirichlet Process Mixture (DPM) model for clustering and image segmentation. The DPM model is a Bayesian nonparametric methodology that relies on MCMC simulations for exploring mixture models with an unknown number of components. The code implements conjugate models with normal structure (conjugate normal-normal DP mixture model). The package's applications are oriented towards the classification of magnetic resonance images according to tissue type or region of interest.

dpmixsim.pdf