CRAN

dpmixsim 0.0-9

Dirichlet Process Mixture Model Simulation for Clustering and Image Segmentation

Released Jul 11, 2018 by Adelino Ferreira da Silva

This package is available for Renjin and there are no known compatibility issues.

Dependencies

cluster 2.0.7-1 oro.nifti 0.9.1

The 'dpmixsim' 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.

Installation

Maven

This package can be included as a dependency from a Java or Scala project by including the following your project's pom.xml file. Read more about embedding Renjin in JVM-based projects.

<dependencies>
  <dependency>
    <groupId>org.renjin.cran</groupId>
    <artifactId>dpmixsim</artifactId>
    <version>0.0-9-b2</version>
  </dependency>
</dependencies>
<repositories>
  <repository>
    <id>bedatadriven</id>
    <name>bedatadriven public repo</name>
    <url>https://nexus.bedatadriven.com/content/groups/public/</url>
  </repository>
</repositories>

View build log

Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:

library('org.renjin.cran:dpmixsim')

Test Results

This package was last tested against Renjin 0.9.2687 on Aug 25, 2018.

Source

R
C
C++

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Release History