Prepare for release

.travis.yml

@@ -8,4 +8,4 @@ r_github_packages:
   - jimhester/covr
 
 after_success:
-  - Rscript -e 'covr::codecov(function_exclusions = c("launch$", "launch_shinystan_demo"), line_exclusions = list("R/zzz.R"))'
+  - Rscript -e 'covr::codecov(function_exclusions = c("launch_shinystan_demo"), line_exclusions = list("R/zzz.R"))'

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: shinystan
 Title: Interactive Visual and Numerical Diagnostics and Posterior Analysis for
     Bayesian Models
-Version: 2.4.0
-Date: 2017-08-01
+Version: 2.5.0
+Date: 2018-04-29
 Authors@R: c(person("Jonah", "Gabry", role = c("aut", "cre"),
     email = "[email protected]"),
       person(family = "Stan Development Team", role = "ctb"),
@@ -30,7 +30,7 @@ Depends:
     R (>= 3.1.0),
     shiny (>= 1.0.3)
 Imports:
-    bayesplot (>= 1.2.0),
+    bayesplot (>= 1.5.0),
     colourpicker,
     DT (>= 0.2),
     dygraphs (>= 1.1.1.2),
@@ -41,7 +41,7 @@ Imports:
     methods,
     reshape2,
     rsconnect (>= 0.4.2),
-    rstan (>= 2.14.1),
+    rstan (>= 2.17.1),
     stats,
     shinyjs (>= 0.6.0),
     shinythemes (>= 1.0.1),
@@ -53,7 +53,7 @@ Suggests:
     coda,
     knitr (>= 1.9),
     rmarkdown (>= 0.8.1),
-    rstanarm (>= 2.15.3),
+    rstanarm (>= 2.17.4),
     testthat
 LazyData: true
 VignetteBuilder: knitr

NEWS.md

@@ -4,7 +4,6 @@
 
 * 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 

README.md

@@ -21,13 +21,13 @@ available via the **shinystan** R package.
 
 ### Installation
 
-* Install from CRAN:
+* Install the latest release from CRAN:
 
 ```r
 install.packages("shinystan")
 ```
 
-* Install from GitHub (requires [devtools](https://github.com/r-lib/devtools) package):
+* Install the development version from GitHub (requires [devtools](https://github.com/r-lib/devtools) package):
 
 ```r
 if (!require("devtools")) {

inst/ShinyStan/ui_files/pp_about.R

@@ -4,14 +4,8 @@ div(
   p(
     strong("The idea behind posterior predictive checking is simple:")
   ),
-  p(
-    style = "text-indent: 10px",
-    em("If our model is a good fit then we should be able to use it to generate")
-  ),
-  p(
-    style = "text-indent: 10px", 
-    em("data that looks a lot like the data we observed.")
-  ),
+  p(em("If our model is a good fit then we should be able to use it to generate")),
+  p(em("data that looks a lot like the data we observed.")),
   br(),
   p(
     "To generate this 'replicated' data we use the",