Update NEWS and references

NEWS.md

@@ -1,3 +1,10 @@
+# shinystan 2.5.0
+
+* 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
+
+
 # shinystan 2.4.0
 
 * `launch_shinystan` is now an S3 generic with methods. This allows developers 
@@ -10,11 +17,14 @@ conflict.
 ### Fixes 
 * 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.
 
 ### New features
+
 * 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).

R/launch_shinystan.R

@@ -35,7 +35,9 @@
 #' @template seealso-as.shinystan 
 #' @template seealso-update_sso 
 #' @template seealso-demo
-#'   
+#' 
+#' @template reference-muth
+#' @template reference-bayesvis
 #'   
 #' @examples
 #' \dontrun{

R/shinystan-objects.R

@@ -40,6 +40,8 @@
 #' @template seealso-generate_quantity
 #' @seealso \code{\link{shinystan-metadata}} to view or change metadata
 #'   associated with a \code{shinystan} object.
+#'   
+#' @template reference-muth
 #' 
 shinystan <- setClass(
   Class = "shinystan",

R/shinystan-package.R

@@ -11,7 +11,7 @@
 # this program; if not, see <http://www.gnu.org/licenses/>.
 
 
-#' 'ShinyStan' interface and \code{shinystan} R package
+#' \pkg{shinystan} R package ('ShinyStan' graphical user interface)
 #'
 #' @docType package
 #' @name shinystan-package
@@ -22,25 +22,27 @@
 #'   \emph{Stan Development Team}
 #' }
 #'
-#' Applied Bayesian data analysis is primarily implemented through the Markov 
-#' chain Monte Carlo (MCMC) algorithms offered by various software packages. 
-#' When analyzing a posterior sample obtained by one of these algorithms the 
+#' Applied Bayesian data analysis is primarily implemented through the Markov
+#' chain Monte Carlo (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 
+#' 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. The
-#' 'ShinyStan' app provides interactive plots and tables helpful for analyzing a
+#' ShinyStan app 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 the 'Shiny' web application framework by 'RStudio' 
-#' and works with the output of MCMC programs written in any programming 
-#' language (and has extended functionality for models fit using the \pkg{rstan}
-#' package and the No-U-Turn sampler).
+#' ShinyStan is powered by the Shiny web application framework by RStudio
+#' (\url{http://shiny.rstudio.com/}) and works with the output of MCMC programs
+#' written in any programming language (and has extended functionality for
+#' models fit using the \pkg{rstan} package and the No-U-Turn sampler).
 #'
-#' @section 'ShinyStan' has extended functionality for 'Stan' models:
+#' @section ShinyStan has extended functionality for Stan models:
 #'
-#' 'Stan' (\url{http://mc-stan.org}) models can be run in \R using the
-#' \pkg{\link[rstan]{rstan}} and \pkg{\link[rstanarm]{rstanarm}} packages.
+#' Stan (\url{http://mc-stan.org}) models can be run in \R using the
+#' \pkg{\link[rstan]{rstan}} package. Other packages like
+#' \pkg{\link[rstanarm]{rstanarm}} and \pkg{\link[brms]{brms}} provide
+#' higher-level interfaces to Stan that use \pkg{rstan} internally.
 #'
 #' @section Saving and sharing:
 #'
@@ -52,7 +54,7 @@
 #'   publication.
 #'
 #'   The \code{\link{deploy_shinystan}} function lets you easily deploy your own
-#'   'ShinyStan' apps online for any of your models using the shinyapps.io 
+#'   ShinyStan apps online for any of your models using the shinyapps.io 
 #'   service from 'RStudio'. Each of your apps (each of your models) will have a
 #'   unique url and will be compatible with most web browsers.
 #'
@@ -66,15 +68,20 @@
 #'  Check out the demo using \code{\link{launch_shinystan_demo}} or try it with
 #'  one of your own models using \code{\link{launch_shinystan}}.
 #'
-#' @section Help and bug reports:
+#' @section Resources:
 #' \itemize{
-#'  \item 'Stan' forums (\url{http://discourse.mc-stan.org})
-#'  \item 'ShinyStan' issue tracker (\url{https://github.com/stan-dev/shinystan/issues})
+#'  \item Web page with online documentation
+#'    (\url{http://mc-stan.org/shinystan})
+#'  \item Stan Forums on Discourse (\url{http://discourse.mc-stan.org})
+#'  \item GitHub issue tracker (\url{https://github.com/stan-dev/shinystan/issues})
 #' }
 #'
 #' @template seealso-as.shinystan
 #' @template seealso-demo
 #' @template seealso-launch
+#' 
+#' @template reference-muth
+#' @template reference-bayesvis
 #'
 #' @import ggplot2
 #' @import methods

man-roxygen/reference-bayesvis.R

@@ -0,0 +1,4 @@
+#' @references Gabry, J., Simpson, D., Vehtari, A., Betancourt, M., and Gelman,
+#'   A. (2018). Visualization in Bayesian workflow. \emph{Journal of the Royal
+#'   Statistical Society Series A}, accepted for publication. arXiv preprint:
+#'   \url{http://arxiv.org/abs/1709.01449}.

man-roxygen/reference-muth.R

@@ -0,0 +1,5 @@
+#' @references
+#' Muth, C., Oravecz, Z., and Gabry, J. (2018)
+#' User-friendly Bayesian regression modeling: A tutorial with rstanarm and shinystan.
+#' \emph{The Quantitative Methods for Psychology}. 14(2), 99--119.
+#' \url{https://www.tqmp.org/RegularArticles/vol14-2/p099/p099.pdf}