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# Copyright 2013-2023 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.package import *
class RCorpcor(RPackage):
"""Efficient Estimation of Covariance and (Partial) Correlation.
Implements a James-Stein-type shrinkage estimator for the covariance
matrix, with separate shrinkage for variances and correlations. The
details of the method are explained in Schafer and Strimmer (2005)
<DOI:10.2202/1544-6115.1175> and Opgen-Rhein and Strimmer (2007)
<DOI:10.2202/1544-6115.1252>. The approach is both computationally as well
as statistically very efficient, it is applicable to "small n, large p"
data, and always returns a positive definite and well-conditioned
covariance matrix. In addition to inferring the covariance matrix the
package also provides shrinkage estimators for partial correlations and
partial variances. The inverse of the covariance and correlation matrix
can be efficiently computed, as well as any arbitrary power of the
shrinkage correlation matrix. Furthermore, functions are available for
fast singular value decomposition, for computing the pseudoinverse, and
for checking the rank and positive definiteness of a matrix."""
cran = "corpcor"
license("GPL-3.0-or-later")
version("1.6.10", sha256="71a04c503c93ec95ddde09abe8c7ddeb36175b7da76365a14b27066383e10e09")
version("1.6.9", sha256="2e4fabd1d3936fecea67fa365233590147ca50bb45cf80efb53a10345a8a23c2")
depends_on("r@3.0.2:", type=("build", "run"))
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