GWnorm: G-Wishart Normalising Constants for Gaussian Graphical Models

Computes G-Wishart normalising constants through a Fourier approach. Either exact analytical results, numerical integration or Monte Carlo estimation are employed. Details at C. Wong, G. Moffa and J. Kuipers (2024), <doi:10.48550/arXiv.2404.06803>. Also includes approximations of the ratio of normalising constants, see details at C. Wong, G. Moffa and J. Kuipers (2025), <doi:10.48550/arXiv.2503.13046>.

Version:	1.0.1
Depends:	R (≥ 4.0.0)
Imports:	igraph, BDgraph, CholWishart, MASS, mvtnorm, hypergeo, gsl, Rcpp (≥ 1.1.1)
LinkingTo:	Rcpp, RcppEigen
Published:	2026-05-27
DOI:	10.32614/CRAN.package.GWnorm
Author:	Ching Wong [aut], Jack Kuipers [aut, cre]
Maintainer:	Jack Kuipers <jack.kuipers at bsse.ethz.ch>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
CRAN checks:	GWnorm results

Documentation:

Reference manual:

GWnorm.html , GWnorm.pdf

Downloads:

Package source:	GWnorm_1.0.1.tar.gz
Windows binaries:	r-devel: GWnorm_1.0.zip, r-release: GWnorm_1.0.zip, r-oldrel: GWnorm_1.0.zip
macOS binaries:	r-release (arm64): GWnorm_1.0.1.tgz, r-oldrel (arm64): GWnorm_1.0.1.tgz, r-release (x86_64): GWnorm_1.0.1.tgz, r-oldrel (x86_64): GWnorm_1.0.1.tgz
Old sources:	GWnorm archive

Linking:

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