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mcmc  

Markov Chain Monte Carlo
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("mcmc", "0.9-8")



Attach the package and use:
library("mcmc")
Maintained by
Charles J. Geyer
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2005-04-05
Latest Update: 2020-03-21
Description:
Simulates continuous distributions of random vectors using Markov chain Monte Carlo (MCMC). Users specify the distribution by an R function that evaluates the log unnormalized density. Algorithms are random walk Metropolis algorithm (function metrop), simulated tempering (function temper), and morphometric random walk Metropolis (Johnson and Geyer, 2012, , function morph.metrop), which achieves geometric ergodicity by change of variable.
How to cite:
Charles J. Geyer (2005). mcmc: Markov Chain Monte Carlo. R package version 0.9-8, https://cran.r-project.org/web/packages/mcmc. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.5-1 (2005-09-17 22:34), 0.5 (2005-04-05 09:38), 0.6 (2009-04-14 19:32), 0.7-2 (2009-09-22 10:22), 0.7-3 (2009-10-09 08:55), 0.7-5 (2010-05-03 20:58), 0.8 (2012-01-15 12:40), 0.9-1 (2012-08-22 07:34), 0.9-2 (2013-03-31 07:54), 0.9-3 (2014-04-02 08:03), 0.9-4 (2015-07-17 00:31), 0.9-5 (2017-04-16 12:23), 0.9-6.1 (2020-02-16 19:29), 0.9-6 (2019-03-10 08:20), 0.9-7 (2020-03-21 20:00), 0.9 (2012-07-03 08:17)
Other packages that cited mcmc R package
View mcmc citation profile
Other R packages that mcmc depends, imports, suggests or enhances
Complete documentation for mcmc
Functions, R codes and Examples using the mcmc R package
Some associated functions: foo . initseq . logit . metrop . morph.metrop . morph . olbm . temper . 
Some associated R codes: initseq.R . metrop.R . morph.R . morph.metrop.R . olbm.R . temper.R .  Full mcmc package functions and examples
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