Package: baygel
Type: Package
Title: Bayesian Estimators for Gaussian Graphical Models
Version: 0.1.0
Date: 2023-01-22
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: 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>.
License: GPL (>= 3)
Imports: Rcpp (>= 1.0.8), RcppArmadillo (>= 0.11.1.1.0)
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Suggests: MASS, pracma
RoxygenNote: 7.2.3
URL: https://github.com/Jarod-Smithy/baygel
NeedsCompilation: yes
Packaged: 2023-01-28 12:11:41 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: 2023-01-30 16:40:04 UTC
Built: R 4.1.3; x86_64-w64-mingw32; 2023-04-17 14:51:51 UTC; windows
Archs: i386, x64
