Bayesian Structure Learning in Graphical Models using Birth-Death MCMC R package BDgraph version 2.74 CRAN Task View: Bayesian (https://CRAN.R-project.org/view=Bayesian) CRAN Task View: GraphicalModels (https://CRAN.R-project.org/view=GraphicalModels) CRAN Task View: HighPerformanceComputing (https://CRAN.R-project.org/view=HighPerformanceComputing) CRAN Task View: MachineLearning (https://CRAN.R-project.org/view=MachineLearning) Advanced statistical tools for Bayesian structure learning in undirected graphical models, accommodating continuous, ordinal, discrete, count, and mixed data. It integrates recent advancements in Bayesian graphical models as presented in the literature, including the works of Mohammadi and Wit (2015) <doi:10.1214/14-BA889>, Mohammadi et al. (2021) <doi:10.1080/01621459.2021.1996377>, Dobra and Mohammadi (2018) <doi:10.1214/18-AOAS1164>, and Mohammadi et al. (2023) <doi:10.48550/arXiv.2307.00127>. Software Depends: R (>= 2.10) Imports: igraph, ggplot2, pROC Suggests: ssgraph, huge, tmvtnorm, skimr, knitr, rmarkdown Reza Mohammadi <a.mohammadi@uva.nl> Comprehensive R Archive Network (CRAN) Reza Mohammadi [aut, cre] (ORCID: <https://orcid.org/0000-0001-9538-0648>), Ernst Wit [aut] (ORCID: <https://orcid.org/0000-0002-3671-9610>), Adrian Dobra [ctb] (ORCID: <https://orcid.org/0000-0001-7793-2197>) GPL (>= 2) 2025-08-29 application/tgz https://CRAN.R-project.org/package=BDgraph doi:10.32614/CRAN.package.BDgraph