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.
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