Dirichlet Process Mixture Model Simulation for Clustering and
Image Segmentation
Description
The 'dpmixsim' 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.