CRAN

vbsr 0.0.5

Variational Bayes Spike Regression Regularized Linear Models

Released Jun 5, 2014 by Benjamin Logsdon

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

Efficient algorithm for solving ultra-sparse regularized regression models using a variational Bayes algorithm with a spike (l0) prior. Algorithm is solved on a path, with coordinate updates, and is capable of generating very sparse models. There are very general model diagnostics for controling type-1 error included in this package.

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>vbsr</artifactId>
    <version>0.0.5-b323</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:vbsr')

Test Results

This package was last tested against Renjin 0.9.2644 on Jun 1, 2018.

Source

R
C

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Release History