CRAN

MoEClust 1.2.2

Gaussian Parsimonious Clustering Models with Covariates and a Noise Component

Released May 15, 2019 by Keefe Murphy

This package can be loaded by Renjin but 10 out 16 tests failed. An older version of this package is more compatible with Renjin.

Dependencies

vcd 1.4-4 matrixStats 0.54.0 mclust 5.4.4 nnet 7.3-12 lattice 0.20-38 mvnfast 0.2.5

Clustering via parsimonious Gaussian Mixtures of Experts using the MoEClust models introduced by Murphy and Murphy (2018) . This package fits finite Gaussian mixture models with a formula interface for supplying gating and/or expert network covariates using a range of parsimonious covariance parameterisations from the GPCM family via the EM/CEM algorithm. Visualisation of the results of such models using generalised pairs plots and the inclusion of an additional noise component is also facilitated.

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>MoEClust</artifactId>
    <version>1.2.2-b1</version>
  </dependency>
</dependencies>
<repositories>
  <repository>
    <id>bedatadriven</id>
    <name>bedatadriven public repo</name>
    <url>https://nexus.bedatadriven.com/content/groups/public/</url>
  </repository>
</repositories>

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Renjin CLI

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

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

Test Results

This package was last tested against Renjin 0.9.2726 on Jul 13, 2019.

Source

R

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Release History