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bgms  

Bayesian Analysis of Graphical Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("bgms", "0.2.0.0")



Attach the package and use:
library("bgms")
Maintained by
Maarten Marsman
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-04-21
Latest Update: 2024-12-05
Description:
Bayesian variable selection methods for analyzing the structure of a Markov Random Field model for a network of binary and/or ordinal variables. Details of the implemented methods can be found in: Marsman and Haslbeck (2023) .
How to cite:
Maarten Marsman (2023). bgms: Bayesian Analysis of Graphical Models. R package version 0.2.0.0, https://cran.r-project.org/web/packages/bgms. Accessed 07 Oct. 2026.
Previous versions and publish date:
(2026-08-04 05:00), 0.1.0 (2023-04-21 09:32), 0.1.1 (2023-09-01 14:20), 0.1.2 (2023-10-13 21:20), 0.1.3.1 (2024-05-15 13:40), 0.1.3 (2024-02-25 19:50), 0.1.4.1 (2024-11-12 17:10), 0.1.4.2 (2024-12-05 11:20), 0.1.4 (2024-10-21 01:00), 0.1.6.0 (2025-09-27 21:10), 0.1.6.1 (2025-10-04 11:20), 0.1.6.2 (2026-01-20 07:10), 0.1.6.3 (2026-02-14 17:50)
Other packages that cited bgms R package
View bgms citation profile
Other R packages that bgms depends, imports, suggests or enhances
Complete documentation for bgms
Functions, R codes and Examples using the bgms R package
Some associated functions: Wenchuan . bgm.em . bgm . bgms-package . mple . mppe . mrfSampler . 
Some associated R codes: RcppExports.R . bgm.R . bgm.em.R . bgms-package.R . datasets.R . maximum_pseudolikelihood.R . maximum_pseudoposterior.R . sampleMRF.R . utility_functions.R .  Full bgms package functions and examples
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