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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