shinystan-package: The ShinyStan interface and shinystan R package

Description

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 the rstan package and the No-U-Turn sampler).

Arguments

docType

package

ShinyStan has extended functionality for Stan models

Stan (http://mc-stan.org) models can be run in R using the rstan package.

Saving and 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 `deploy_shinystan` function, which lets you easily deploy your own ShinyStan apps online using RStudio's ShinyApps (https://www.shinyapps.io) 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.

License

The shinystan package is open source licensed under the GNU Public License, version 3 (GPLv3).

Demo

Check out the demo using launch_shinystan_demo or try it with one of your own models using launch_shinystan.