CRAN

NominalLogisticBiplot 0.2

Biplot representations of categorical data

Released May 2, 2014 by Julio Cesar Hernandez Sanchez

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

Dependencies

mirt 1.28 MASS 7.3-50 gmodels 2.16.2

Analysis of a matrix of polytomous items using Nominal Logistic Biplots (NLB) according to Hernandez-Sanchez and Vicente-Villardon (2013). The NLB procedure extends the binary logistic biplot to nominal (polytomous) data. The individuals are represented as points on a plane and the variables are represented as convex prediction regions rather than vectors as in a classical or binary biplot. Using the methods from Computational Geometry, the set of prediction regions is converted to a set of points in such a way that the prediction for each individual is established by its closest "category point". Then interpretation is based on distances rather than on projections. In this package we implement the geometry of such a representation and construct computational algorithms for the estimation of parameters and the calculation of prediction regions.

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>NominalLogisticBiplot</artifactId>
    <version>0.2-b43</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:NominalLogisticBiplot')

Test Results

This package was last tested against Renjin 0.9.2644 on Jun 2, 2018.

Source

R

View GitHub Mirror

Release History