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 (≥ 0.11.1.1.0), pracma, statmod, stats |
| LinkingTo: | Rcpp, RcppArmadillo, RcppProgress |
| Suggests: | MASS |
| Published: | 2023-07-08 |
| Author: | Jarod Smith  [aut,
cre],
Mohammad Arashi
[aut],
Andriette Bekker
[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_0.2.0.tar.gz |
| Windows binaries: | r-devel: baygel_0.2.0.zip, r-release: baygel_0.2.0.zip, r-oldrel: baygel_0.2.0.zip |
| 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 |
Linking:
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