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SBICgraph  

Structural Bayesian Information Criterion for Graphical Models
View on CRAN: Click here


Download and install SBICgraph package within the R console
Install from CRAN:
install.packages("SBICgraph")

Install from Github:
library("remotes")
install_github("cran/SBICgraph")

Install by package version:
library("remotes")
install_version("SBICgraph", "1.0.0")



Attach the package and use:
library("SBICgraph")
Maintained by
Quang Nguyen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-03-02
Latest Update: 2021-03-02
Description:
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.
How to cite:
Quang Nguyen (2021). SBICgraph: Structural Bayesian Information Criterion for Graphical Models. R package version 1.0.0, https://cran.r-project.org/web/packages/SBICgraph. Accessed 17 Jul. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited SBICgraph R package
View SBICgraph citation profile
Other R packages that SBICgraph depends, imports, suggests or enhances
Complete documentation for SBICgraph
Functions, R codes and Examples using the SBICgraph R package
Some associated functions: addition . comparison . deletion . mle . modelset . sbic . sggm . simulate . 
Some associated R codes: candidateset.R . comparison.R . dataSimulate.R . mle.R . sGGM.R . sbic.R .  Full SBICgraph package functions and examples
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