Package: BayesianGLasso 0.2.0

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>.

Authors:Patrick Trainor [aut, cre], Hao Wang [aut]

BayesianGLasso_0.2.0.tar.gz
BayesianGLasso_0.2.0.zip(r-4.7)BayesianGLasso_0.2.0.zip(r-4.6)BayesianGLasso_0.2.0.zip(r-4.5)
BayesianGLasso_0.2.0.tgz(r-4.6-any)BayesianGLasso_0.2.0.tgz(r-4.5-any)
BayesianGLasso_0.2.0.tar.gz(r-4.7-any)BayesianGLasso_0.2.0.tar.gz(r-4.6-any)
BayesianGLasso_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BayesianGLasso/json (API)

# Install 'BayesianGLasso' in R:

install.packages('BayesianGLasso', repos = c('https://trainorp.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.41 score 2 stars 13 scripts 38 downloads 1 exports 2 dependencies

Last updated from:8ffa9ba9fc. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	93
source / vignettes	OK	151
linux-release-x86_64	OK	97
macos-release-arm64	OK	119
macos-oldrel-arm64	OK	74
windows-devel	OK	64
windows-release	OK	60
windows-oldrel	OK	93
wasm-release	OK	83