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.


coda 0.19-1 Matrix 1.2-11

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>

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Test Results

This package was last tested against Renjin 0.8.2523 on Nov 12, 2017.



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