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
CRAN checks: BayesianGLasso results

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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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