R: Extracting and Visualizing Bayesian Graphical Models

# Extracting and Visualizing Bayesian Graphical Models

## Documentation for package ‘easybgm’ version 0.4.0

- DESCRIPTION file
- Package README

## Help Pages

bgm_extract | Extract the results of a Bayesian analysis of networks
bgm_fit | Fit a Bayesian analysis of networks
centrality | Plot strength centralities and 95% highest density interval
clusterBayesfactor | Calculate Clustering Bayes Factors for when using the Stochastic Block Model as an edge prior
complexity_probs | Plot posterior complexity probabilities
easybgm | Bayesian analysis of networks
easybgm_compare | Compare networks across groups using Bayesian inference
edgeevidence | Edge evidence plot
HDI | Plot of interaction parameters and their 95% highest density intervals
network | Network plot
plot_centrality | Plot strength centralities and 95% highest density interval
plot_complexity_probabilities | Plot posterior complexity probabilities
plot_edgeevidence | Edge evidence plot
plot_network | Network plot
plot_parameterHDI | Plot of interaction parameters and their 95% highest density intervals
plot_prior_sensitivity | Plot sensitivity to edge inclusion prior setting
plot_structure | Structure plot
plot_structure_probabilities | Plot Posterior Structure Probabilities
print.easybgm | Print method for 'easybgm' objects
print.easybgm_compare | Print method for 'easybgm_compare' objects
prior_sensitivity | Plot sensitivity to edge inclusion prior setting
structure | Structure plot
structure_probs | Plot Posterior Structure Probabilities
summary.easybgm | Summary method for 'easybgm' objects
summary.easybgm_compare | Summary method for 'easybgm_compare' objects