8ebf242e8f
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.
27 lines
1.3 KiB
Python
27 lines
1.3 KiB
Python
# Copyright 2013-2021 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 import *
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class RTmvnsim(RPackage):
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"""Truncated Multivariate Normal Simulation
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Importance sampling from the truncated multivariate normal using the GHK
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(Geweke-Hajivassiliou-Keane) simulator. Unlike Gibbs sampling which can get
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stuck in one truncation sub-region depending on initial values, this
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package allows truncation based on disjoint regions that are created by
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truncation of absolute values. The GHK algorithm uses simple Cholesky
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transformation followed by recursive simulation of univariate truncated
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normals hence there are also no convergence issues. Importance sample is
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returned along with sampling weights, based on which, one can calculate
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integrals over truncated regions for multivariate normals."""
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homepage = "https://cloud.r-project.org/package=tmvnsim"
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url = "https://cloud.r-project.org/src/contrib/tmvnsim_1.0-2.tar.gz"
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list_url = "https://cloud.r-project.org/src/contrib/Archive/tmvnsim"
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version('1.0-2', sha256='97f63d0bab3b240cc7bdbe6e6e74e90ad25a4382a345ee51a26fe3959edeba0f')
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