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.

Version: 0.0-8
Depends: R (≥ 2.10.0), oro.nifti, cluster
Published: 2012-07-25
Author: Adelino Ferreira da Silva
Maintainer: Adelino Ferreira da Silva <afs at fct.unl.pt>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: NEWS
In views: Cluster, MedicalImaging
CRAN checks: dpmixsim results


Reference manual: dpmixsim.pdf
Package source: dpmixsim_0.0-8.tar.gz
Windows binaries: r-devel: dpmixsim_0.0-8.zip, r-release: dpmixsim_0.0-8.zip, r-oldrel: dpmixsim_0.0-8.zip
OS X El Capitan binaries: r-release: dpmixsim_0.0-8.tgz
OS X Mavericks binaries: r-oldrel: dpmixsim_0.0-8.tgz
Old sources: dpmixsim archive


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