CRAN

AdaptiveSparsity 1.4

Adaptive Sparsity Models

Released Jan 3, 2014 by Kristen Zygmunt, Eleanor Wong, Tom Fletcher

This package can be loaded by Renjin but there was an error compiling C/FORTRAN sources and all tests failed.

Dependencies

Rcpp

Implements Figueiredo EM algorithm for adaptive sparsity (Jeffreys prior) (see Figueiredo, M.A.T.; , "Adaptive sparseness for supervised learning," Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol.25, no.9, pp. 1150- 1159, Sept. 2003) and Wong algorithm for adaptively sparse gaussian geometric models (see Wong, Eleanor, Suyash Awate, and P. Thomas Fletcher. "Adaptive Sparsity in Gaussian Graphical Models." In Proceedings of the 30th International Conference on Machine Learning (ICML-13), pp. 311-319. 2013.)

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>AdaptiveSparsity</artifactId>
    <version>1.4-b247</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:AdaptiveSparsity')

Test Results

This package was last tested against Renjin 0.8.2397 on Jun 8, 2017.

Source

R
C
C++

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Release History