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abglasso: Adaptive Bayesian Graphical Lasso

Implements a Bayesian adaptive graphical lasso data-augmented block Gibbs sampler. The sampler simulates the posterior distribution of precision matrices of a Gaussian Graphical Model. This sampler was adapted from the original MATLAB routine proposed in Wang (2012) <doi:10.1214/12-BA729>.

Version: 0.1.1
Imports: MASS, pracma, stats, statmod
Suggests: testthat
Published: 2021-07-13
DOI: 10.32614/CRAN.package.abglasso
Author: Jarod Smith ORCID iD [aut, cre], Mohammad Arashi ORCID iD [aut], Andriette Bekker ORCID iD [aut]
Maintainer: Jarod Smith <jarodsmith706 at gmail.com>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
In views: Bayesian
CRAN checks: abglasso results

Documentation:

Reference manual: abglasso.pdf

Downloads:

Package source: abglasso_0.1.1.tar.gz
Windows binaries: r-devel: abglasso_0.1.1.zip, r-release: abglasso_0.1.1.zip, r-oldrel: abglasso_0.1.1.zip
macOS binaries: r-release (arm64): abglasso_0.1.1.tgz, r-oldrel (arm64): abglasso_0.1.1.tgz, r-release (x86_64): abglasso_0.1.1.tgz, r-oldrel (x86_64): abglasso_0.1.1.tgz
Old sources: abglasso archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.