New website with online documentation: http://mc-stan.org/shinystan
Fixed problem with extracting info from fits reconstructed from CSV files (#128,#158), thanks to @martinmodrak
launch_shinystan is now an S3 generic with methods. This allows developers of packages that use shinystan to create their own launch_shinystan methods instead of using a different function name or creating a naming conflict.Fix various issues resulting in errors for models fit using static HMC (thanks to Cole Monnahan).
Deprecate burnin argument to as.shinystan. Use warmup instead. Only relevant for models not fit using Stan.
Add NUTS energy diagnostic plots to Diagnose page
Allowing passing sampler_params to as.shinystan. This makes it possible to display sampler diagnositcs for HMC/NUTS even if not using Stan’s implementation of those algorithms (thanks to Cole Monnahan).
shinystan::launch_shinystan_demo() now works without first having to load the package with a call to librarydeploy_shinystan preventing some ShinyStan apps from being deployedpars to the as.shinystan method for stanfit objects, allowing a subset of parameters to be selected for inclusion in the resulting shinystan object.drop_parameters function for removing parameters from a shinystan object (useful for very large objects when you only want to look at a subset of parameters).rstanarm::pp_check can be called.yrep from global environment for PPcheckas.shinystan to S4 generic with methodsImports in DESCRIPTION.update_sso function can be used to ensure that old shinystan objects have an internal structure compatible with this release.Version 2.0.0 has a new look, a new(ish) name, and a lot of new functionality. Many bugs have also been fixed (see GitHub issue tracker).
deploy_shinystan function lets you easily deploy ShinyStan apps to RStudio’s shinyapps.io for any of your models. Each of your apps (i.e. each of your models) will have a unique url.