35 lines
1.5 KiB
Python
35 lines
1.5 KiB
Python
# Copyright 2013-2023 Lawrence Livermore National Security, LLC and other
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# Spack Project Developers. See the top-level COPYRIGHT file for details.
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#
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# SPDX-License-Identifier: (Apache-2.0 OR MIT)
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from spack.package import *
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class RMcmcpack(RPackage):
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"""Markov Chain Monte Carlo (MCMC) Package.
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Contains functions to perform Bayesian inference using posterior simulation
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for a number of statistical models. Most simulation is done in compiled C++
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written in the Scythe Statistical Library Version 1.0.3. All models return
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'coda' mcmc objects that can then be summarized using the 'coda' package.
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Some useful utility functions such as density functions, pseudo-random
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number generators for statistical distributions, a general purpose
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Metropolis sampling algorithm, and tools for visualization are provided."""
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cran = "MCMCpack"
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version("1.6-3", sha256="cb14ba20690b31fd813b05565484c866425f072a5ad99a5cbf1da63588958db3")
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version("1.6-0", sha256="b5b9493457d11d4dca12f7732bd1b3eb1443852977c8ee78393126f13deaf29b")
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version("1.5-0", sha256="795ffd3d62bf14d3ecb3f5307bd329cd75798cf4b270ff0e768bc71a35de0ace")
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depends_on("r@3.6:", type=("build", "run"))
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depends_on("r-coda@0.11-3:", type=("build", "run"))
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depends_on("r-lattice", type=("build", "run"))
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depends_on("r-mcmc", type=("build", "run"))
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depends_on("r-quantreg", type=("build", "run"))
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depends_on("r-mass", type=("build", "run"), when="@:1.6-0")
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conflicts("%gcc@:3")
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