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author | Ricardo Wurmus <rekado@elephly.net> | 2020-02-26 10:12:36 +0100 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2020-02-26 10:12:36 +0100 |
commit | 849f6bc20bcb3280b3dee9e5555224d32796b575 (patch) | |
tree | 37cac1115e0ec5df414db92934b5f19c1252402f /gnu/packages | |
parent | f3de8b6c8a5a7e1404b234de37cac5ef71484c24 (diff) | |
download | patches-849f6bc20bcb3280b3dee9e5555224d32796b575.tar patches-849f6bc20bcb3280b3dee9e5555224d32796b575.tar.gz |
gnu: Add r-rstanarm.
* gnu/packages/cran.scm (r-rstanarm): New variable.
Diffstat (limited to 'gnu/packages')
-rw-r--r-- | gnu/packages/cran.scm | 41 |
1 files changed, 41 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm index e6a350d07e..7ff282bde1 100644 --- a/gnu/packages/cran.scm +++ b/gnu/packages/cran.scm @@ -20520,3 +20520,44 @@ optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.") (license license:gpl3+))) + +(define-public r-rstanarm + (package + (name "r-rstanarm") + (version "2.19.3") + (source + (origin + (method url-fetch) + (uri (cran-uri "rstanarm" version)) + (sha256 + (base32 + "0gxjq8bdlvdd8kn3dhp12xlymdab036r7n12lzmd3xlkl4cnxq3s")))) + (properties `((upstream-name . "rstanarm"))) + (build-system r-build-system) + (inputs + `(("pandoc" ,ghc-pandoc) + ("pandoc-citeproc" ,ghc-pandoc-citeproc))) + (propagated-inputs + `(("r-bayesplot" ,r-bayesplot) + ("r-bh" ,r-bh) + ("r-ggplot2" ,r-ggplot2) + ("r-lme4" ,r-lme4) + ("r-loo" ,r-loo) + ("r-matrix" ,r-matrix) + ("r-nlme" ,r-nlme) + ("r-rcpp" ,r-rcpp) + ("r-rcppeigen" ,r-rcppeigen) + ("r-rcppparallel" ,r-rcppparallel) + ("r-rstan" ,r-rstan) + ("r-rstantools" ,r-rstantools) + ("r-shinystan" ,r-shinystan) + ("r-stanheaders" ,r-stanheaders) + ("r-survival" ,r-survival))) + (home-page "https://mc-stan.org/rstanarm/") + (synopsis "Bayesian applied regression modeling via Stan") + (description + "This package estimates previously compiled regression models using the +@code{rstan} package, which provides the R interface to the Stan C++ library +for Bayesian estimation. Users specify models via the customary R syntax with +a formula and @code{data.frame} plus some additional arguments for priors.") + (license license:gpl3+))) |