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adaptMCMC  

Implementation of a Generic Adaptive Monte Carlo Markov Chain Sampler
View on CRAN: Click here


Download and install adaptMCMC package within the R console
Install from CRAN:
install.packages("adaptMCMC")

Install from Github:
library("remotes")
install_github("cran/adaptMCMC")

Install by package version:
library("remotes")
install_version("adaptMCMC", "1.5")



Attach the package and use:
library("adaptMCMC")
Maintained by
Andreas Scheidegger
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2011-12-09
Latest Update: 2024-01-29
Description:
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.
How to cite:
Andreas Scheidegger (2011). adaptMCMC: Implementation of a Generic Adaptive Monte Carlo Markov Chain Sampler. R package version 1.5, https://cran.r-project.org/web/packages/adaptMCMC. Accessed 09 Mar. 2026.
Previous versions and publish date:
1.0.2 (2012-01-03 17:16), 1.0.3 (2012-05-16 13:49), 1.0 (2011-12-09 16:56), 1.1 (2012-06-22 11:34), 1.2 (2017-07-01 00:19), 1.3 (2018-01-14 17:41), 1.4 (2021-03-29 11:00)
Other packages that cited adaptMCMC R package
View adaptMCMC citation profile
Other R packages that adaptMCMC depends, imports, suggests or enhances
Complete documentation for adaptMCMC
Functions, R codes and Examples using the adaptMCMC R package
Some associated functions: MCMC.add.samples . MCMC . MCMC.parallel . convert.to.coda . genericMCMC-package . 
Some associated R codes: Adaptive_MCMC.R .  Full adaptMCMC package functions and examples
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