CRAN

GPCSIV 0.1.0

GPCSIV, Generalized Principal Component of Symbolic Interval variables

Released Sep 15, 2013 by Brahim Brahim

Dependencies

scatterplot3d 0.3.4 sqldf 0.4-11

This package implements an extension of principal component analysis (PCA) tailored to handle multiple data tables. It can handle Big Data in the sense that the variation in massive data can be described by intervals [a, b] and multiple tables.

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>GPCSIV</artifactId>
    <version>0.1.0-b38</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:GPCSIV')

Test Results

This package was last tested against Renjin 0.8.2504 on Oct 30, 2017.

• Judge1-examples
• Judge2-examples
• Judge3-examples
• Resdata-examples
• gpca-examples
• oils-examples
• video1-examples
• video2-examples
• video3-examples

Source

View GitHub Mirror

Release History

• 0.1.0