ShinyStan v2.0.011 Aug 2015
ShinyStan provides immediate, informative, customizable visual and numerical summaries of model parameters and convergence diagnostics for MCMC simulations. The ShinyStan graphical user interface is available via the shinystan R package. Try the online demo.
Installing the shinystan R package
Install from CRAN:
If this fails, try adding the arguments
Install from GitHub (requires devtools package):
devtools::install_github("stan-dev/shinystan", build_vignettes = TRUE)
To take advantage of all the features in the shinystan package, it is also recommended to install the shinyapps package. You can do this by running
Applied Bayesian data analysis is primarily implemented through the MCMC algorithms offered by various software packages. When analyzing a posterior sample obtained by one of these algorithms the first step is to check for signs that the chains have converged to the target distribution and and also for signs that the algorithm might require tuning or might be ill-suited for the given model. There may also be theoretical problems or practical inefficiencies with the specification of the model.
ShinyStan provides interactive plots and tables helpful for analyzing a posterior sample, with particular attention to identifying potential problems with the performance of the MCMC algorithm or the specification of the model. ShinyStan is powered by RStudio’s Shiny web application framework and works with the output of MCMC programs written in any programming language (and has extended functionality for models fit using RStan and the No-U-Turn sampler).
Saving and deploying (sharing)
The shinystan package allows you to store the basic components of an entire project (code, posterior samples, graphs, tables, notes) in a single object. Users can save many of the plots as ggplot2 objects for further customization and easy integration in reports or post-processing for publication.
The new version of shinystan also provides the
which lets you easily deploy your own ShinyStan apps online using RStudio’s
ShinyApps service for any of
your models. Each of your apps (each of your models) will have a unique url
and is compatible with Safari, Firefox, Chrome, and most other browsers.
The shinystan R package and ShinyStan interface are open source licensed under the GNU Public License, version 3 (GPLv3).