adaptMCMC 1.3

Implementation of a Generic Adaptive Monte Carlo Markov Chain Sampler

Released Jan 14, 2018 by Andreas Scheidegger

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


Matrix 1.2-12 coda 0.19-1

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.



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.

    <name>bedatadriven public repo</name>

View build log

Renjin CLI

If you're using Renjin from the command line, you load this library by invoking:


Test Results

This package was last tested against Renjin 0.9.2600 on Mar 5, 2018.



View GitHub Mirror

Release History