CRAN

glmgraph 1.0.3

Graph-Constrained Regularization for Sparse Generalized Linear Models

Released Jul 19, 2015 by Li Chen

This package can be loaded by Renjin but 9 out 10 tests failed.

Dependencies

We propose to use sparse regression model to achieve variable selection while accounting for graph-constraints among coefficients. Different linear combination of a sparsity penalty(L1) and a smoothness(MCP) penalty has been used, which induces both sparsity of the solution and certain smoothness on the linear coefficients.

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>glmgraph</artifactId>
    <version>1.0.3-b67</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:glmgraph')

Test Results

This package was last tested against Renjin 0.9.2689 on Aug 27, 2018.

Source

C++

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