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.
|Author||Adelino Ferreira da Silva <email@example.com>|
|Maintainer||Adelino Ferreira da Silva <firstname.lastname@example.org>|
|License||GPL version 2 or newer|
|Package repository||View on R-Forge|
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