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authorLevi Baber <baberlevi@gmail.com>2018-11-19 20:42:45 -0600
committerAdam J. Stewart <ajstewart426@gmail.com>2018-11-19 20:42:45 -0600
commit535035b22352970312523e89245752ee4d8abf8f (patch)
tree852ee990fa6243504047321c53bea7c2ed67a347
parent19723768656d752901f43f3affcbc9fb89a22cd4 (diff)
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r-rrpp: new package (#9887)
-rw-r--r--var/spack/repos/builtin/packages/r-rrpp/package.py29
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diff --git a/var/spack/repos/builtin/packages/r-rrpp/package.py b/var/spack/repos/builtin/packages/r-rrpp/package.py
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+# Copyright 2013-2018 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 RRrpp(RPackage):
+ """Linear model calculations are made for many random versions of data.
+
+ Using residual randomization in a permutation procedure, sums of
+ squares are calculated over many permutations to generate empirical
+ probability distributions for evaluating model effects. This method
+ is described by Collyer, Sekora, & Adams (2015)
+ <doi:10.1038/hdy.2014.75>. Additionally, coefficients, statistics,
+ fitted values, and residuals generated over many permutations can be
+ used for various procedures including pairwise tests, prediction,
+ classification, and model comparison. This package should provide
+ most tools one could need for the analysis of high-dimensional data,
+ especially in ecology and evolutionary biology, but certainly
+ other fields, as well."""
+
+ homepage = "https://github.com/mlcollyer/RRPP"
+ url = "https://cran.r-project.org/src/contrib/RRPP_0.3.0.tar.gz"
+ list_url = "https://cron.r-project.org/src/contrib/Archive/RRPP"
+
+ version('0.3.0', sha256='34fea6ce7a78e4f38398d3b99585bab11a8171bc8b9a4e461b6d984ed1373739')