dpmixsim: Dirichlet Process Mixture model simulation for clustering and image segmentation
Version 0.0-5

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>
MaintainerAdelino Ferreira da Silva <afs@fct.unl.pt>
LicenseGPL version 2 or newer
Version0.0-5
Package repositoryView on R-Forge
Installation Install the latest version of this package by entering the following in R:
install.packages("dpmixsim", repos="http://R-Forge.R-project.org")

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dpmixsim documentation built on May 31, 2017, 3:47 a.m.