CRAN

DCEM 0.0.2

Clustering for Multivariate and Univariate Data Using Expectation Maximization Algorithm

Released Apr 5, 2019 by Sharma Parichit

This package can be loaded by Renjin but 1 out 10 tests failed.

Dependencies

MASS 7.3-51.4 mvtnorm 1.0-10 matrixcalc 1.0-3

Implements the Expectation Maximisation (EM) algorithm for clustering finite gaussian mixture models for both multivariate and univariate datasets. The initialization is done by randomly selecting the samples from the dataset as the mean of the Gaussian(s). This version improves the parameter initialization on big datasets. The algorithm returns a set of Gaussian parameters-posterior probabilities, mean, co-variance matrices (multivariate data)/standard-deviation (for univariate datasets) and priors. Reference: Hasan Kurban, Mark Jenne, Mehmet M. Dalkilic (2016) . This work is partially supported by NCI Grant 1R01CA213466-01.

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>DCEM</artifactId>
    <version>0.0.2-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:DCEM')

Test Results

This package was last tested against Renjin 0.9.2725 on May 4, 2019.

Source

R

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Release History