Package: abglasso 0.1.1

abglasso: Adaptive Bayesian Graphical Lasso

Implements a Bayesian adaptive graphical lasso data-augmented block Gibbs sampler. The sampler simulates the posterior distribution of precision matrices of a Gaussian Graphical Model. This sampler was adapted from the original MATLAB routine proposed in Wang (2012) <doi:10.1214/12-BA729>.

Authors:Jarod Smith [aut, cre], Mohammad Arashi [aut], Andriette Bekker [aut]

abglasso_0.1.1.tar.gz
abglasso_0.1.1.zip(r-4.7-any)abglasso_0.1.1.zip(r-4.6-any)abglasso_0.1.1.zip(r-4.5-any)
abglasso_0.1.1.tgz(r-4.6-any)abglasso_0.1.1.tgz(r-4.5-any)
abglasso_0.1.1.tar.gz(r-4.7-any)abglasso_0.1.1.tar.gz(r-4.6-any)
abglasso_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
abglasso/json (API)

# Install 'abglasso' in R:
install.packages('abglasso', repos = c('https://jarod-smithy.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

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

1.70 score 1 scripts 531 downloads 1 exports 3 dependencies

Last updated from:284d05fc27. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE182
source / vignettesOK135
linux-releaseNOTE94
macos-releaseNOTE82
macos-oldrelNOTE69
windows-develNOTE58
windows-releaseNOTE64
windows-oldrelNOTE56
wasm-releaseOK102

Exports:BayesGlassoBlock

Dependencies:MASSpracmastatmod