baygel: Bayesian Estimators for Gaussian Graphical Models

This R package offers a Bayesian graphical ridge and a naïve Bayesian adaptive graphical elastic net data-augmented block Gibbs sampler. These samplers facilitate the simulation of the posterior distribution of precision matrices for Gaussian distributed data. These samplers were originally proposed in two separate studies, both detailing their methodologies and applications: Smith, Arashi, and Bekker (2022) <doi:10.48550/arXiv.2210.16290> and Smith, Bekker, and Arashi (2023) <doi:10.48550/arXiv.2306.14199>.

Version: 0.2.0
Imports: Rcpp (≥ 1.0.8), RcppArmadillo (≥, pracma, statmod, stats
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Suggests: MASS
Published: 2023-07-08
Author: Jarod Smith ORCID iD [aut, cre], Mohammad Arashi ORCID iD [aut], Andriette Bekker ORCID iD [aut]
Maintainer: Jarod Smith <jarodsmith706 at>
License: GPL (≥ 3)
NeedsCompilation: yes
Materials: README
CRAN checks: baygel results


Reference manual: baygel.pdf


Package source: baygel_0.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): baygel_0.2.0.tgz, r-oldrel (arm64): baygel_0.2.0.tgz, r-release (x86_64): baygel_0.2.0.tgz, r-oldrel (x86_64): baygel_0.2.0.tgz
Old sources: baygel archive


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