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>.
Version: 2.73 Imports: igraph, ggplot2, pROC Suggests: ssgraph, huge, tmvtnorm, skimr, knitr, rmarkdown Published: 2024-08-23 DOI: 10.32614/CRAN.package.BDgraph Author: Reza Mohammadi [aut, cre], Ernst Wit [aut], Adrian Dobra [ctb] Maintainer: Reza Mohammadi <a.mohammadi at uva.nl> License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: https://www.uva.nl/profile/a.mohammadi NeedsCompilation: yes Citation: BDgraph citation info Materials: README NEWS In views: Bayesian, GraphicalModels, HighPerformanceComputing, MachineLearning CRAN checks: BDgraph results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=BDgraph to link to this page.
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