Add code to check the R package and update DESCRIPTION.

.github/workflows/R-package.yml

@@ -17,4 +17,6 @@ jobs:
     steps:
       - uses: "actions/checkout@v2"
       - uses: "r-lib/actions/setup-r@v2"
-
+      - uses: r-lib/actions/check-r-package@v2
+        with:
+          working-directory: R-package

R-package/.Rbuildignore

@@ -1,3 +1,4 @@
 ^gptoolsStan\.Rproj$
 ^R-package\.Rproj$
 ^\.Rproj\.user$
+vignettes/getting_started

R-package/DESCRIPTION

@@ -1,17 +1,23 @@
 Package: gptoolsStan
-Title: Gaussian Processes on Graphs and Lattices in Stan.
+Title: Gaussian Processes on Graphs and Lattices in Stan
 Version: 0.1
 Authors@R:
     person("Till", "Hoffmann", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0003-4403-0722"))
     person("Jukka-Pekka", "Onnela", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0001-6613-8668"))
-Description: Gaussian processes are flexible distributions to model functional data. Whilst theoretically appealing, they are computationally cumbersome except for small datasets. This package implements two methods for scaling GP inference in Stan: (a) a sparse approximation of the likelihood that is generally applicable and (b) an exact method for regularly spaced data modeled by stationary kernels using fast Fourier methods.
+Description: Gaussian processes are flexible distributions to model functional data. Whilst
+    theoretically appealing, they are computationally cumbersome except for small datasets.
+    This package implements two methods for scaling GP inference in Stan. First, a sparse
+    approximation of the likelihood that is generally applicable and, second, an exact method for
+    regularly spaced data modeled by stationary kernels using fast Fourier methods.
 License: BSD-3-Clause
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
 RoxygenNote: 7.2.3
-Suggests: 
+Suggests:
     knitr,
-    rmarkdown
+    rmarkdown,
+    cmdstanr
 VignetteBuilder: knitr
+Remotes: https://mc-stan.org/r-packages/