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baygel: Bayesian Shrinkage Estimators for Precision Matrices in Gaussian Graphical Models
This R package offers block Gibbs samplers for the Bayesian (adaptive) graphical lasso, ridge, and naive elastic net priors. These samplers facilitate the simulation of the posterior distribution of precision matrices for Gaussian distributed data and were originally proposed by: Wang (2012) <doi:10.1214/12-BA729>; Smith et al. (2022) <doi:10.48550/arXiv.2210.16290> and Smith et al. (2023) <doi:10.48550/arXiv.2306.14199>, respectively.
Getting started
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Package details |
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| 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> |
| License | GPL (>= 3) |
| Version | 0.3.0 |
| URL | https://github.com/Jarod-Smithy/baygel |
| Package repository | View on CRAN |
| Installation |
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