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new package: r-tmvnsim (#21104)

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Importance sampling from the truncated multivariate normal using the GHK
(Geweke-Hajivassiliou-Keane) simulator. Unlike Gibbs sampling which can
get stuck in one truncation sub-region depending on initial values, this
package allows truncation based on disjoint regions that are created by
truncation of absolute values. The GHK algorithm uses simple Cholesky
transformation followed by recursive simulation of univariate truncated
normals hence there are also no convergence issues. Importance sample is
returned along with sampling weights, based on which, one can calculate
integrals over truncated regions for multivariate normals.
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Glenn Johnson 2021-01-17 11:13:47 -06:00 committed by GitHub
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# 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 RTmvnsim(RPackage):
"""Truncated Multivariate Normal Simulation
Importance sampling from the truncated multivariate normal using the GHK
(Geweke-Hajivassiliou-Keane) simulator. Unlike Gibbs sampling which can get
stuck in one truncation sub-region depending on initial values, this
package allows truncation based on disjoint regions that are created by
truncation of absolute values. The GHK algorithm uses simple Cholesky
transformation followed by recursive simulation of univariate truncated
normals hence there are also no convergence issues. Importance sample is
returned along with sampling weights, based on which, one can calculate
integrals over truncated regions for multivariate normals."""
homepage = "https://cloud.r-project.org/package=tmvnsim"
url = "https://cloud.r-project.org/src/contrib/tmvnsim_1.0-2.tar.gz"
list_url = "https://cloud.r-project.org/src/contrib/Archive/tmvnsim"
version('1.0-2', sha256='97f63d0bab3b240cc7bdbe6e6e74e90ad25a4382a345ee51a26fe3959edeba0f')