Resources for ggmcmc

ggmcmc is an R package aimed at providing 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.

Development

ggmcmc is developed in github and has attracted attention from several fields of science.

• Raise an issue, being either a bug report, a question on how to use specific functions, a request for improvement, a clarification, ask for documentation or provide ideas.
• Read the list of improvements, changes and news

Documentation

• Article at the Journal of Statistical Software (and internal site)
• Documentation on Using ggmcmc
• Posts using ggmcmc in my blog:
  • Families and batches of parameters in Bayesian inference: how to treat them using ggmcmc
  • Comparison of Rhat versions: clarifying formulas for the potential scale reduction factor and its implications
  • Processing Stan samples with ggmcmc

Impact

• Citations
• Articles in this site refering to the package.

Citation

Fernández-i-Marín, X. (2016). ggmcmc: Analysis of MCMC samples and Bayesian inference. Journal of Statistical Software, 70(9), 1-20. 10.18637/jss.v070.i09

citation in different formats

Acknowledgements

I would like to thank code contributions and ideas from Zachary M. Jones, Julien Cornebise, Max Joseph, and ideas from Dieter Menne, Bill Dixon, Christopher Gandrud, Barret Schloerke and GitHub users knokknok, akrawitz, Justina (Juste), stefanherzog, Brian Stock, Jonas Kristoffer Lindeløv, Jakob Fiksel and Sébastien Rochette.