SBICgraph: Structural Bayesian Information Criterion for Graphical Models
This is the implementation of the novel structural Bayesian information criterion by Zhou, 2020 (under review). In this method, the prior structure is modeled and incorporated into the Bayesian information criterion framework. Additionally, we also provide the implementation of a two-step algorithm to generate the candidate model pool.
| Version: | 1.0.0 |
| Imports: | glmnet, MASS, network |
| Suggests: | knitr, rmarkdown |
| Published: | 2021-03-02 |
| DOI: | 10.32614/CRAN.package.SBICgraph |
| Author: | Quang Nguyen 
[cre, aut],
Jie Zhou [aut],
Anne Hoen [aut],
Jiang Gui [aut] |
| Maintainer: | Quang Nguyen <Quang.P.Nguyen.GR at dartmouth.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | SBICgraph results |
Documentation:
| Reference manual: | SBICgraph.html , SBICgraph.pdf |
| Vignettes: |
overview (source, R code) |
Downloads:
| Package source: | SBICgraph_1.0.0.tar.gz |
| Windows binaries: | r-devel: SBICgraph_1.0.0.zip, r-release: SBICgraph_1.0.0.zip, r-oldrel: SBICgraph_1.0.0.zip |
| macOS binaries: | r-release (arm64): SBICgraph_1.0.0.tgz, r-oldrel (arm64): SBICgraph_1.0.0.tgz, r-release (x86_64): SBICgraph_1.0.0.tgz, r-oldrel (x86_64): SBICgraph_1.0.0.tgz |
Linking:
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