BayesianGLasso: Bayesian Graphical Lasso

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
In views:	Bayesian
CRAN checks:	BayesianGLasso results

Documentation:

Reference manual:

BayesianGLasso.pdf

Downloads:

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 (arm64): BayesianGLasso_0.2.0.tgz, r-oldrel (arm64): BayesianGLasso_0.2.0.tgz, r-release (x86_64): BayesianGLasso_0.2.0.tgz, r-oldrel (x86_64): BayesianGLasso_0.2.0.tgz

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