Package: dpmixsim
Version: 0.0-6
Date: 2011-06-14
Title: Dirichlet Process Mixture model simulation for clustering and
image segmentation
Author: Adelino Ferreira da Silva <afs@fct.unl.pt>
Maintainer: Adelino Ferreira da Silva <afs@fct.unl.pt>
Depends: R (>= 2.10.0), oro.nifti, cluster
Description: 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.
License: GPL (>= 2)
Repository: CRAN
Packaged: 2011-06-14 08:04:11 UTC; afs
Date/Publication: 2011-06-15 18:00:25

Package: dpmixsim
Version: 0.0-7
Date: 2011-06-20
Title: Dirichlet Process Mixture model simulation for clustering and
image segmentation
Author: Adelino Ferreira da Silva <afs@fct.unl.pt>
Maintainer: Adelino Ferreira da Silva <afs@fct.unl.pt>
Depends: R (>= 2.10.0), oro.nifti, cluster
Description: 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.
License: GPL (>= 2)
Repository: CRAN
Packaged: 2011-06-20 08:35:06 UTC; afs
Date/Publication: 2011-06-20 09:43:07

Package: dpmixsim
Version: 0.0-8
Date: 2012-07-24
Title: Dirichlet Process Mixture model simulation for clustering and
image segmentation
Author: Adelino Ferreira da Silva <afs@fct.unl.pt>
Maintainer: Adelino Ferreira da Silva <afs@fct.unl.pt>
Depends: R (>= 2.10.0), oro.nifti, cluster
Description: 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.
License: GPL (>= 2)
Repository: CRAN
Packaged: 2012-07-24 15:33:15 UTC; arfs
Date/Publication: 2012-07-25 06:29:31