49 lines
2.5 KiB
Python
49 lines
2.5 KiB
Python
##############################################################################
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# Copyright (c) 2013-2016, Lawrence Livermore National Security, LLC.
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# Produced at the Lawrence Livermore National Laboratory.
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#
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# This file is part of Spack.
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# Created by Todd Gamblin, tgamblin@llnl.gov, All rights reserved.
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# LLNL-CODE-647188
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#
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# For details, see https://github.com/llnl/spack
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# Please also see the NOTICE and LICENSE files for our notice and the LGPL.
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#
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU Lesser General Public License (as
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# published by the Free Software Foundation) version 2.1, February 1999.
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#
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# This program is distributed in the hope that it will be useful, but
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# WITHOUT ANY WARRANTY; without even the IMPLIED WARRANTY OF
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the terms and
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# conditions of the GNU Lesser General Public License for more details.
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#
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# You should have received a copy of the GNU Lesser General Public
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# License along with this program; if not, write to the Free Software
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# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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##############################################################################
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from spack import *
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class RStanheaders(RPackage):
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"""The C++ header files of the Stan project are provided by this package,
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but it contains no R code, vignettes, or function documentation. There is a
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shared object containing part of the CVODES library, but it is not
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accessible from R. StanHeaders is only useful for developers who want to
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utilize the LinkingTo directive of their package's DESCRIPTION file to
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build on the Stan library without incurring unnecessary dependencies. The
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Stan project develops a probabilistic programming language that implements
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full or approximate Bayesian statistical inference via Markov Chain Monte
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Carlo or variational methods and implements (optionally penalized) maximum
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likelihood estimation via optimization. The Stan library includes an
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advanced automatic differentiation scheme, templated statistical and linear
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algebra functions that can handle the automatically differentiable scalar
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types (and doubles, ints, etc.), and a parser for the Stan language. The
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'rstan' package provides user-facing R functions to parse, compile, test,
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estimate, and analyze Stan models."""
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homepage = "http://mc-stan.org/"
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url = "https://cran.r-project.org/src/contrib/StanHeaders_2.10.0-2.tar.gz"
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version('2.10.0-2', '9d09b1e9278f08768f7a988ad9082d57')
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