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ggmcmc
View on CRAN: Click
here
Download and install ggmcmc package within the R console
Install from CRAN:
install.packages("ggmcmc")
Install from Github:
library("remotes")
install_github("cran/ggmcmc") Install by package version:
library("remotes")
install_version("ggmcmc", "1.5.1.2") Attach the package and use:
library("ggmcmc")
Maintained by
Xavier Fernández i Marín
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-09-05
Latest Update: 2021-02-10
Description:
Tools for assessing and diagnosing convergence of
Markov Chain Monte Carlo simulations, as well as for graphically display
results from full MCMC analysis. The package also facilitates the graphical
interpretation of models by providing flexible functions to plot the
results against observed variables, and functions to work with
hierarchical/multilevel batches of parameters
(Fern
How to cite:
Xavier Fernández i Marín (2012). ggmcmc: Tools for Analyzing MCMC Simulations from Bayesian Inference. R package version 1.5.1.2, https://cran.r-project.org/web/packages/ggmcmc. Accessed 22 Sep. 2026.
Previous versions and publish date:
(2026-07-09 07:43), 0.2 (2012-09-05 14:16), 0.3 (2012-12-09 09:05), 0.4.1 (2013-07-30 08:27), 0.4.2 (2013-08-12 07:37), 0.4 (2013-07-05 16:54), 0.5.1 (2013-10-03 19:41), 0.5 (2013-09-14 17:02), 0.6 (2014-12-30 13:34), 0.7.1 (2015-07-29 20:48), 0.7.2 (2015-09-03 16:53), 0.7.3 (2016-01-04 12:47), 0.8 (2016-03-14 18:10), 1.0 (2016-05-12 14:47), 1.1.1 (2019-01-23 19:57), 1.1 (2016-06-28 23:48), 1.2 (2019-02-16 00:10), 1.3 (2019-07-03 11:30), 1.4.1 (2020-04-02 13:00), 1.5.0 (2020-08-29 09:50), 1.5.1.1 (2021-02-10 11:50)
Other packages that cited ggmcmc R package
View ggmcmc citation profile
Other R packages that ggmcmc depends,
imports, suggests or enhances
Complete documentation for ggmcmc
Functions, R codes and Examples using
the ggmcmc R package
Some associated functions: ac . binary . calc_bin . ci . custom.sort . get_family . ggmcmc . ggs . ggs_Rhat . ggs_autocorrelation . ggs_caterpillar . ggs_chain . ggs_compare_partial . ggs_crosscorrelation . ggs_density . ggs_diagnostics . ggs_effective . ggs_geweke . ggs_grb . ggs_histogram . ggs_pairs . ggs_pcp . ggs_ppmean . ggs_ppsd . ggs_rocplot . ggs_running . ggs_separation . ggs_traceplot . gl_unq . linear . plab . radon . roc_calc . s.binary . s . s.y.rep . sde0f . y.binary . y .
Some associated R codes: data.R . functions.R . ggmcmc.R . ggs.R . ggs_Rhat.R . ggs_autocorrelation.R . ggs_caterpillar.R . ggs_compare_partial.R . ggs_crosscorrelation.R . ggs_density.R . ggs_diagnostics.R . ggs_effective.R . ggs_geweke.R . ggs_grb.R . ggs_histogram.R . ggs_pairs.R . ggs_pcp.R . ggs_ppmean.R . ggs_ppsd.R . ggs_rocplot.R . ggs_running.R . ggs_separation.R . ggs_traceplot.R . globals.R . help.R . Full ggmcmc package functions and examples
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