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authorGlenn Johnson <glenn-johnson@uiowa.edu>2021-04-20 04:14:18 -0500
committerGitHub <noreply@github.com>2021-04-20 11:14:18 +0200
commit2b3efb40caba45df7eae12e006ff71e9e27e7e77 (patch)
tree22bb7f93c1284febb38dfb267ec1e209a74144e5 /var
parent54f919018d84cd737942ebedac6af2e5b06dd287 (diff)
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r-mcmc: new package (#23106)
Diffstat (limited to 'var')
-rw-r--r--var/spack/repos/builtin/packages/r-mcmc/package.py25
1 files changed, 25 insertions, 0 deletions
diff --git a/var/spack/repos/builtin/packages/r-mcmc/package.py b/var/spack/repos/builtin/packages/r-mcmc/package.py
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+++ b/var/spack/repos/builtin/packages/r-mcmc/package.py
@@ -0,0 +1,25 @@
+# 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 RMcmc(RPackage):
+ """Markov Chain Monte Carlo:
+
+ Simulates continuous distributions of random vectors using Markov chain
+ Monte Carlo (MCMC). Users specify the distribution by an R function that
+ evaluates the log unnormalized density. Algorithms are random walk
+ Metropolis algorithm (function metrop), simulated tempering (function
+ temper), and morphometric random walk Metropolis (Johnson and Geyer, 2012,
+ <doi:10.1214/12-AOS1048>, function morph.metrop), which achieves geometric
+ ergodicity by change of variable."""
+
+ homepage = "http://www.stat.umn.edu/geyer/mcmc/"
+ cran = "mcmc"
+
+ version('0.9-7', sha256='b7c4d3d5f9364c67a4a3cd49296a61c315ad9bd49324a22deccbacb314aa8260')
+
+ depends_on('r@3.0.2:', type=('build', 'run'))