baygel: Bayesian Estimators for Gaussian Graphical Models

Implements a Bayesian graphical ridge data-augmented block Gibbs sampler. The sampler simulates the posterior distribution of precision matrices of a Gaussian Graphical Model. This sampler is proposed in Smith, Arashi, and Bekker (2022) <doi:10.48550/arXiv.2210.16290>.

Version: 0.1.0
Imports: Rcpp (≥ 1.0.8), RcppArmadillo (≥ 0.11.1.1.0)
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Suggests: MASS, pracma
Published: 2023-01-30
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)
URL: https://github.com/Jarod-Smithy/baygel
NeedsCompilation: yes
Materials: README
CRAN checks: baygel results

Documentation:

Reference manual: baygel.pdf

Downloads:

Package source: baygel_0.1.0.tar.gz
Windows binaries: r-devel: baygel_0.1.0.zip, r-release: baygel_0.1.0.zip, r-oldrel: baygel_0.1.0.zip
macOS binaries: r-release (arm64): baygel_0.1.0.tgz, r-oldrel (arm64): baygel_0.1.0.tgz, r-release (x86_64): baygel_0.1.0.tgz, r-oldrel (x86_64): baygel_0.1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=baygel to link to this page.