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:
abglasso_0.1.1.tar.gz
abglasso_0.1.1.zip(r-4.5)abglasso_0.1.1.zip(r-4.4)abglasso_0.1.1.zip(r-4.3)
abglasso_0.1.1.tgz(r-4.4-any)abglasso_0.1.1.tgz(r-4.3-any)
abglasso_0.1.1.tar.gz(r-4.5-noble)abglasso_0.1.1.tar.gz(r-4.4-noble)
abglasso_0.1.1.tgz(r-4.4-emscripten)abglasso_0.1.1.tgz(r-4.3-emscripten)
abglasso.pdf |abglasso.html✨
abglasso/json (API)
NEWS
| # Install 'abglasso' in R: |
| install.packages('abglasso', repos = c('https://jarod-smithy.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:284d05fc27. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 25 2024 |
| R-4.5-win | NOTE | Oct 25 2024 |
| R-4.5-linux | NOTE | Oct 25 2024 |
| R-4.4-win | NOTE | Oct 25 2024 |
| R-4.4-mac | NOTE | Oct 25 2024 |
| R-4.3-win | NOTE | Oct 25 2024 |
| R-4.3-mac | NOTE | Oct 25 2024 |
Exports:BayesGlassoBlock
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Adaptive Bayesian graphical lasso MCMC sampler | BayesGlassoBlock |
