Implements a data-augmented block Gibbs sampler for simulating the posterior distribution of concentration matrices for specifying the topology and parameterization of a Gaussian Graphical Model (GGM). This sampler was originally proposed in Wang (2012) <doi:10.1214/12-BA729>.
| Version: | 0.2.0 |
| Depends: | R (≥ 3.0.0) |
| Imports: | statmod, MASS |
| Published: | 2017-07-19 |
| Author: | Patrick Trainor [aut, cre], Hao Wang [aut] |
| Maintainer: | Patrick Trainor <patrick.trainor at louisville.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | BayesianGLasso results |
| Reference manual: | BayesianGLasso.pdf |
| Package source: | BayesianGLasso_0.2.0.tar.gz |
| Windows binaries: | r-devel: BayesianGLasso_0.2.0.zip, r-release: BayesianGLasso_0.2.0.zip, r-oldrel: BayesianGLasso_0.2.0.zip |
| macOS binaries: | r-release: BayesianGLasso_0.2.0.tgz, r-oldrel: BayesianGLasso_0.2.0.tgz |
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