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author | Lars-Dominik Braun <ldb@leibniz-psychology.org> | 2020-02-04 14:08:37 +0100 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2020-02-22 20:42:12 +0100 |
commit | d228795210de4535d817f8fbc696e82c0800e2f3 (patch) | |
tree | 7a87d6c6f4313228616c9ea2275530a535a110db /gnu/packages/cran.scm | |
parent | 8b217feb3b242484de1917a1c19402281eb95cf7 (diff) | |
download | guix-d228795210de4535d817f8fbc696e82c0800e2f3.tar.gz |
gnu: Add r-stanheaders.
* gnu/packages/cran.scm (r-stanheaders): New variable.
Diffstat (limited to 'gnu/packages/cran.scm')
-rw-r--r-- | gnu/packages/cran.scm | 36 |
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))) |