adaptMCMC 1.3

Implementation of a Generic Adaptive Monte Carlo Markov Chain Sampler

Released Jan 14, 2018 by Andreas Scheidegger

This package cannot yet be used with Renjin because there was a problem building the package using Renjin's toolchain. View Build Log An older version of this package is more compatible with Renjin.


coda 0.19-1 Matrix 1.2-12

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.



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