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authorLars-Dominik Braun <ldb@leibniz-psychology.org>2020-02-04 14:08:37 +0100
committerRicardo Wurmus <rekado@elephly.net>2020-02-22 20:42:12 +0100
commitd228795210de4535d817f8fbc696e82c0800e2f3 (patch)
tree7a87d6c6f4313228616c9ea2275530a535a110db /gnu
parent8b217feb3b242484de1917a1c19402281eb95cf7 (diff)
downloadguix-d228795210de4535d817f8fbc696e82c0800e2f3.tar.gz
gnu: Add r-stanheaders.
* gnu/packages/cran.scm (r-stanheaders): New variable.
Diffstat (limited to 'gnu')
-rw-r--r--gnu/packages/cran.scm36
1 files changed, 36 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm
index b69311a39b..1f778d73d1 100644
--- a/gnu/packages/cran.scm
+++ b/gnu/packages/cran.scm
@@ -19766,3 +19766,39 @@ offers additional cost functions, cross validation, and other extensions
 beyond traditional structural equation models.  It also contains a function to
 perform @dfn{exploratory mediation} (XMed).")
     (license license:gpl2+)))
+
+(define-public r-stanheaders
+  (package
+    (name "r-stanheaders")
+    (version "2.19.0")
+    (source
+     (origin
+       (method url-fetch)
+       (uri (cran-uri "StanHeaders" version))
+       (sha256
+        (base32
+         "0kyka130sin4nbji7p840394ynhmaynv9jyi94ddbplj83i2nhx3"))))
+    (properties `((upstream-name . "StanHeaders")))
+    (build-system r-build-system)
+    (inputs `(("pandoc" ,ghc-pandoc)))
+    (native-inputs `(("gfortran" ,gfortran)))
+    (home-page "https://mc-stan.org/")
+    (synopsis "C++ header files for Stan")
+    (description
+     "The C++ header files of the Stan project are provided by this package.
+There is a shared object containing part of the @code{CVODES} library, but it
+is not accessible from R.  @code{r-stanheaders} is only useful for developers
+who want to utilize the @code{LinkingTo} directive of their package's
+DESCRIPTION file to build on the Stan library without incurring unnecessary
+dependencies.
+
+The Stan project develops a probabilistic programming language that implements
+full or approximate Bayesian statistical inference via Markov Chain Monte
+Carlo or variational methods and implements (optionally penalized) maximum
+likelihood estimation via optimization.  The Stan library includes an advanced
+automatic differentiation scheme, templated statistical and linear algebra
+functions that can handle the automatically differentiable scalar types (and
+doubles, ints, etc.), and a parser for the Stan language.  The @code{r-rstan}
+package provides user-facing R functions to parse, compile, test, estimate,
+and analyze Stan models.")
+    (license license:bsd-3)))