dpmixsim: Dirichlet Process Mixture model simulation for clustering and image segmentation
Version 0.0-8

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.

Getting started

Package details

AuthorAdelino Ferreira da Silva <afs@fct.unl.pt>
Date of publication2012-07-25 06:29:31
MaintainerAdelino Ferreira da Silva <afs@fct.unl.pt>
LicenseGPL (>= 2)
Version0.0-8
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("dpmixsim")

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dpmixsim documentation built on May 29, 2017, 11:04 p.m.