Tools for Analyzing MCMC Simulations from Bayesian Inference

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 (Fernández-i-Marín, 2016 ).


ggmcmc

ggmcmc is a tool 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.

To install or update, run:

install.packages("ggmcmc", dependencies=TRUE)

Check the main page with resources for ggmcmc.

Report bugs, request improvements, ask questions or provide ideas at the issues page.

Reference manual

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install.packages("ggmcmc")

1.5.1.2 by Xavier Fernández i Marín, a year ago


http://xavier-fim.net/packages/ggmcmc/, https://github.com/xfim/ggmcmc/


Report a bug at https://github.com/xfim/ggmcmc/issues/


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


Authors: Xavier Fernández i Marín [aut, cre] (ORCID:


Documentation:   PDF Manual  


GPL-2 license


Imports GGally, MASS

Depends on dplyr, tidyr, ggplot2

Suggests coda, knitr, rmarkdown, ggthemes, gridExtra, Cairo, extrafont


Imported by EcoDiet, MixSIAR, PLMIX, bml, bspcov, missingHE, oHMMed, rbioacc, serodynamics.

Suggested by CausalMixGPD, afdx, airGR, crmPack, metamisc, nimbleExtra, runMCMCbtadjust.


See at CRAN