CRAN

adaptMCMC 1.2

Implementation of a Generic Adaptive Monte Carlo Markov Chain Sampler

Released Jun 30, 2017 by Andreas Scheidegger, ,

This package can be loaded by Renjin but 2 out 4 tests failed.

Dependencies

coda 0.19-1 Matrix 1.2-10

Enables sampling from arbitrary distributions if the log density is known up to a constant; a common situation in the context of Bayesian inference. The implemented sampling algorithm was proposed by Vihola (2012) and achieves often a high efficiency by tuning the proposal distributions to a user defined acceptance rate.

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>adaptMCMC</artifactId>
    <version>1.2-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:adaptMCMC')

Test Results

This package was last tested against Renjin 0.8.2411 on Jul 2, 2017.

Source

R

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Release History