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rgm  

Advanced Inference with Random Graphical Models
View on CRAN: Click here


Download and install rgm package within the R console
Install from CRAN:
install.packages("rgm")

Install from Github:
library("remotes")
install_github("cran/rgm")

Install by package version:
library("remotes")
install_version("rgm", "1.0.4")



Attach the package and use:
library("rgm")
Maintained by
Francisco Richter
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-01-12
Latest Update: 2024-01-12
Description:
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." .
How to cite:
Francisco Richter (2024). rgm: Advanced Inference with Random Graphical Models. R package version 1.0.4, https://cran.r-project.org/web/packages/rgm. Accessed 06 Nov. 2024.
Previous versions and publish date:
1.0.1 (2024-01-12 10:50), 1.0.3 (2024-03-12 15:10)
Other packages that cited rgm R package
View rgm citation profile
Other R packages that rgm depends, imports, suggests or enhances
Complete documentation for rgm
Functions, R codes and Examples using the rgm R package
Some associated functions: rgm . sim.rgm . 
Some associated R codes: RcppExports.R . rgm-auxilaryfunctions.R . rgm.R . sim.rgm.R .  Full rgm package functions and examples
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