Implements state-of-the-art Random Graphical Models (RGMs) for multivariate data analysis across multiple environments, offering tools for exploring network interactions and structural relationships. Capabilities include joint inference across environments, integration of external covariates, and a Bayesian framework for uncertainty quantification. Applicable in various fields, including microbiome analysis. Methods based on Vinciotti, V., Wit, E., & Richter, F. (2023). "Random Graphical Model of Microbiome Interactions in Related Environments." <doi:10.48550/arXiv.2304.01956>.
Version: 1.0.4 Depends: R (≥ 3.5.0) Imports: truncnorm, BDgraph, MASS, huge, ggplot2, stats, pROC, reshape2 LinkingTo: Rcpp Suggests: knitr, rmarkdown Published: 2024-03-21 DOI: 10.32614/CRAN.package.rgm Author: Francisco Richter [aut, cre], Veronica Vinciotti [ctb], Ernst Wit [ctb] Maintainer: Francisco Richter <richtf at usi.ch> BugReports: https://github.com/franciscorichter/rgm/issues License: MIT + file LICENSE NeedsCompilation: yes Materials: README CRAN checks: rgm results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=rgm to link to this page.
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