Package: SBICgraph 1.0.0

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.

Authors:Quang Nguyen [cre, aut], Jie Zhou [aut], Anne Hoen [aut], Jiang Gui [aut]

SBICgraph_1.0.0.tar.gz
SBICgraph_1.0.0.zip(r-4.7)SBICgraph_1.0.0.zip(r-4.6)SBICgraph_1.0.0.zip(r-4.5)
SBICgraph_1.0.0.tgz(r-4.6-any)SBICgraph_1.0.0.tgz(r-4.5-any)
SBICgraph_1.0.0.tar.gz(r-4.7-any)SBICgraph_1.0.0.tar.gz(r-4.6-any)
SBICgraph_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SBICgraph/json (API)
NEWS

# Install 'SBICgraph' in R:
install.packages('SBICgraph', repos = c('https://qpmnguyen.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.

2.70 score 3 scripts 213 downloads 6 exports 24 dependencies

Last updated from:cc38c4238c. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE134
source / vignettesOK184
linux-release-x86_64NOTE128
macos-release-arm64NOTE154
macos-oldrel-arm64NOTE133
windows-develNOTE127
windows-releaseNOTE81
windows-oldrelNOTE95
wasm-releaseOK99

Exports:comparisonmlemodelsetsbicsggmsimulate

Dependencies:clicodacodetoolsforeachglmnetglueiteratorslatticelifecyclemagrittrMASSMatrixnetworkpillarpkgconfigRcppRcppEigenrlangshapestatnet.commonsurvivaltibbleutf8vctrs

Overview of using SBIC for network models

Rendered fromoverview.Rmdusingknitr::rmarkdownon May 10 2026.

Last update: 2021-03-02
Started: 2021-03-02