Package: baygel
Type: Package
Title: Bayesian Estimators for Gaussian Graphical Models
Version: 0.2.0
Date: 2023-07-07
Authors@R: c(person("Jarod", "Smith", email = "jarodsmith706@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-4235-6147")),
  person("Mohammad", "Arashi", email = "arashi@um.ac.ir", role = "aut", comment = c(ORCID = "0000-0002-5881-9241")),
  person("Andriette", "Bekker", email = "andriette.bekker@up.ac.za", role = "aut", comment = c(ORCID = "0000-0003-4793-5674")))
Description: 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>.
License: GPL (>= 3)
Imports: Rcpp (>= 1.0.8), RcppArmadillo (>= 0.11.1.1.0), pracma,
        statmod, stats
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Suggests: MASS
RoxygenNote: 7.2.3
Encoding: UTF-8
URL: https://github.com/Jarod-Smithy/baygel
NeedsCompilation: yes
Packaged: 2023-07-07 15:18:51 UTC; QXZ0GWG
Author: Jarod Smith [aut, cre] (<https://orcid.org/0000-0003-4235-6147>),
  Mohammad Arashi [aut] (<https://orcid.org/0000-0002-5881-9241>),
  Andriette Bekker [aut] (<https://orcid.org/0000-0003-4793-5674>)
Maintainer: Jarod Smith <jarodsmith706@gmail.com>
Repository: CRAN
Date/Publication: 2023-07-08 11:00:02 UTC
