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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 |
Reference manual: | rgm.pdf |
Vignettes: |
rgm |
Package source: | rgm_1.0.4.tar.gz |
Windows binaries: | r-devel: rgm_1.0.4.zip, r-release: rgm_1.0.4.zip, r-oldrel: rgm_1.0.4.zip |
macOS binaries: | r-release (arm64): rgm_1.0.4.tgz, r-oldrel (arm64): rgm_1.0.4.tgz, r-release (x86_64): rgm_1.0.4.tgz, r-oldrel (x86_64): rgm_1.0.4.tgz |
Old sources: | rgm archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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