CRAN

missSBM 0.2.0

Handling Missing Data in Stochastic Block Models

Released Jun 8, 2019 by Julien Chiquet

This package can be loaded by Renjin but 6 out 10 tests failed.

Dependencies

RcppArmadillo 0.9.500.2.0 magrittr 1.5 nloptr 1.2.1 ape 5.3 corrplot 0.84 igraph 1.2.4.1 Rcpp R6 2.4.0

When a network is partially observed (here, NAs in the adjacency matrix rather than 1 or 0 due to missing information between node pairs), it is possible to account for the underlying process that generates those NAs. 'missSBM' adjusts the popular stochastic block model from network data sampled under various missing data conditions, as described in Tabouy, Barbillon and Chiquet (2019) .

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>missSBM</artifactId>
    <version>0.2.0-b1</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:missSBM')

Test Results

This package was last tested against Renjin 0.9.2726 on Jul 13, 2019.

Source

R
C
C++

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Release History