r-brms: new package (#23233)

1 files changed, 52 insertions, 0 deletions

diff --git a/var/spack/repos/builtin/packages/r-brms/package.py b/var/spack/repos/builtin/packages/r-brms/package.py
new file mode 100644
index 0000000000..7da8d8fa12
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+++ b/var/spack/repos/builtin/packages/r-brms/package.py
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+# Copyright 2013-2021 Lawrence Livermore National Security, LLC and other
+# Spack Project Developers. See the top-level COPYRIGHT file for details.
+#
+# SPDX-License-Identifier: (Apache-2.0 OR MIT)
+
+from spack import *
+
+
+class RBrms(RPackage):
+    """Bayesian Regression Models using 'Stan':
+
+    Fit Bayesian generalized (non-)linear multivariate multilevel models using
+    'Stan' for full Bayesian inference. A wide range of distributions and link
+    functions are supported, allowing users to fit - among others - linear,
+    robust linear, count data, survival, response times, ordinal,
+    zero-inflated, hurdle, and even self-defined mixture models all in a
+    multilevel context. Further modeling options include non-linear and smooth
+    terms, auto-correlation structures, censored data, meta-analytic standard
+    errors, and quite a few more. In addition, all parameters of the response
+    distribution can be predicted in order to perform distributional
+    regression. Prior specifications are flexible and explicitly encourage
+    users to apply prior distributions that actually reflect their beliefs.
+    Model fit can easily be assessed and compared with posterior predictive
+    checks and leave-one-out cross-validation.  References: Burkner (2017)
+    <doi:10.18637/jss.v080.i01>; Burkner (2018) <doi:10.32614/RJ-2018-017>;
+    Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>."""
+
+    homepage = "https://github.com/paul-buerkner/brms"
+    cran     = "brms"
+
+    version('2.15.0', sha256='c11701d1d8758590b74bb845b568b736e4455a81b114c7dfde0b27b7bd1bcc2f')
+
+    depends_on('r@3.5.0:', type=('build', 'run'))
+    depends_on('r-rcpp@0.12.0:', type=('build', 'run'))
+    depends_on('r-rstan@2.19.2:', type=('build', 'run'))
+    depends_on('r-ggplot2@2.0.0:', type=('build', 'run'))
+    depends_on('r-loo@2.3.1:', type=('build', 'run'))
+    depends_on('r-matrix@1.1.1:', type=('build', 'run'))
+    depends_on('r-mgcv@1.8-13:', type=('build', 'run'))
+    depends_on('r-rstantools@2.1.1:', type=('build', 'run'))
+    depends_on('r-bayesplot@1.5.0:', type=('build', 'run'))
+    depends_on('r-shinystan@2.4.0:', type=('build', 'run'))
+    depends_on('r-projpred@2.0.0:', type=('build', 'run'))
+    depends_on('r-bridgesampling@0.3-0:', type=('build', 'run'))
+    depends_on('r-glue@1.3.0:', type=('build', 'run'))
+    depends_on('r-future@1.19.0:', type=('build', 'run'))
+    depends_on('r-matrixstats', type=('build', 'run'))
+    depends_on('r-nleqslv', type=('build', 'run'))
+    depends_on('r-nlme', type=('build', 'run'))
+    depends_on('r-coda', type=('build', 'run'))
+    depends_on('r-abind', type=('build', 'run'))
+    depends_on('r-backports', type=('build', 'run'))