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>.">

BDgraph: Bayesian Structure Learning in Graphical Models using Birth-Death MCMC (original) (raw)

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 ORCID iD [aut, cre], Ernst Wit ORCID iD [aut], Adrian Dobra ORCID iD [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

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