Stochastic Approximation Monte Carlo (SAMC) Sampler and Methods

Stochastic Approximation Monte Carlo (SAMC) is one of the celebrated Markov chain Monte Carlo (MCMC) algorithms. It is known to be capable of sampling from multimodal or doubly intractable distributions. We provide generic SAMC samplers for continuous distributions. User-specified densities in R and C++ are both supported. We also provide functions for specific problems that exploit SAMC computation. See Liang et al (2010) for complete introduction to the method.


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install.packages("SAMCpack")

0.1.1 by Kisung You, 3 months ago


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


Authors: Yichen Cheng [aut] , Ick Hoon Jin [aut] , Faming Liang [aut] , Kisung You [aut, cre]


Documentation:   PDF Manual  


GPL (>= 3) license


Imports Rcpp, RcppXPtrUtils, utils, Rdpack

Suggests knitr, rmarkdown, microbenchmark, pander, geoR, RandomFields

Linking to Rcpp, RcppArmadillo


See at CRAN