Implementation of a Generic Adaptive Monte Carlo Markov Chain Sampler

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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install.packages("adaptMCMC")

1.3 by Andreas Scheidegger, a year ago


https://github.com/scheidan/adaptMCMC


Report a bug at https://github.com/scheidan/adaptMCMC/issues


Browse source code at https://github.com/cran/adaptMCMC


Authors: Andreas Scheidegger , <[email protected]> , <[email protected]>


Documentation:   PDF Manual  


GPL (>= 2) license


Depends on parallel, coda, Matrix


Imported by POUMM.

Suggested by GUTS.


See at CRAN