Tools to Visualize, Manipulate, and Summarize MCMC Output

Performs key functions for MCMC analysis using minimal code - visualizes, manipulates, and summarizes MCMC output. Functions support simple and straightforward subsetting of model parameters within the calls, and produce presentable and 'publication-ready' output. MCMC output may be derived from Bayesian model output fit with JAGS, Stan, or other MCMC samplers.




  • Fix whitespace issue in MCMCplot when many parameters are plotted and large fig dimensions are used
  • Fix label alginment issue in MCMCplot when horiz = FALSE and large numbers of parameters are plotted


  • Fix bug that prevented parameters from being sorted when using matrix input for MCMCtrace
  • Add support for objects produced with the jagsUI package


  • MCMCtrace now takes matrix input (as with the other functions). One chain is assumed when matrix input is used.


  • Fix bug that produced errors when using the jags.parallel function in the R2jags package.
  • All functions - when ISB = FALSE, params argument now takes the form of regular expressions
  • Examples for MCMCtrace no longer open up external programs (pdf viewer) per CRAN policy


  • MCMCpstr function now added. Function returns summary output for a specified function while preserving structure of parameters (i.e., scalar, vector, matrix, array).
  • MCMCtrace now takes a priors argument to visualize prior/posterior overlap. If specified, the prior (user specified as this information is not contained within the MCMC output) for a specified parameter is plotted on the same plot as the posterior output. Percent overlap between posterior and prior is also calculated and displayed.
  • Fix bug in MCMCchains that caused incorrect alphabetization of parameter names when output from R2jags was used.


  • MCMCsummary greatly speed up calculation of Rhat values for objects with large numbers of parameters
  • MCMCchains now takes the argument mcmc.list. If specified, mcmc.list object returned rather than a matrix.


  • Fix bug in MCMCsummary that displayed the same result twice when selecting only a single output parameter of interest
  • Fix bug in MCMCplot that displayed the axis label too close to tick labels when horiz = FALSE and tick labels were very long
  • MCMCsummary Rhat values always round to 2 digits
  • MCMCsummary output from func argument rounded to specified digits for rest of output
  • MCMCsummary now takes a func_name argument. If specified, column displaying output from func will be labeled with this name. If not specified, column will be labeled 'func'.
  • MCMCplot change argument x_axis_text_sz and x_tick_text_sz to axis_text_sz and tick_text_sz respectively


  • Specification of parameters of interest now works slightly differently. The argument ISB (Ignore Square Bracket) has now been added. By default ISB = TRUE - params and excl match exactly to parameter names by default (ignoring square brackets). When ISB = FALSE, square brackets will not be ignored, and will match on partial names (as when using grep). This applies to all functions.
  • MCMCsummary now takes a func argument. If a function is specified, it will be evaluated for all specified parameters and specified in the MCMCsummary output.
  • MCMCsummary speed greatly increased. Parameters of interest are now sorted before calculations are made. Rhat values are no longer masked, but rather not calculated when Rhat = FALSE. These changes result in dramatic speed ups for large objects.
  • MCMCsummary bug fixed that caused function to fail when only one chain was run
  • MCMCsummary standard deviation added to summary output for each parameter.
  • MCMCsummary number of effective samples added to summary output for each parameter. Default is n.eff = FALSE (metric will not be calculated or displayed).
  • MCMCtrace default is now to write trace plots to pdf. Default number of iterations changed to 5000 from 2000.
  • MCMCplot y-axis labels now vertical when horiz = FALSE to improve readability.
  • MCMCplot bug that resulted in poor plot dimension choices in some circumstances now fixed.
  • MCMC_data now contains three chains with 6000 iterations each.
  • Error message now added about functions not taking objects produced from jags.samples function in the coda package. coda.samples should be used instead.


  • Fix bug in MCMCplot which incorrectly shaded parameter estimates when plotted vertically
  • MCMCsummary now displays estimates for deviance with MCMC output fits with R2jags


  • Fix bug in MCMCsummary to do with Cholesky decomposition and calculating Rhat.
  • Speed up processing of MCMCsummary for certain object types.
  • Fix minor documentation errors in help files for several functions.
  • MCMCplot labels now start at top and go down (more intuitive).
  • MCMCtrace now plots only the last 2000 iterations of the posterior chains by default. The argument is now number of iterations to be plotted, rather than the starting iteration to plot. As such, MCMCtrace argument iter_st (start iteration) changed to iter (number of iterations from end).
  • Add horiz argument to MCMCplot - caterpillar plots can now be plotted to run vertically rather than horizontally. Parameters are plotted left to right when plotted vertically.
  • Remove extended lines on axes for MCMCplot - axes lines only goes to the end of ticks now.


  • Initial release

Reference manual

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0.11.0 by Casey Youngflesh, a month ago

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Browse source code at

Authors: Casey Youngflesh [aut, cre] (<>>), Christian Che-Castaldo [ctb], Tyler Hardy [ctb]

Documentation:   PDF Manual  

Task views: Bayesian Inference

GPL-3 license

Imports coda, rstan, grDevices, graphics, stats, overlapping

Suggests knitr, rmarkdown, testthat

See at CRAN