Extracting and Visualizing Bayesian Graphical Models
Extract the results of a Bayesian analysis of networks
Fit a Bayesian analysis of networks
Plot strength centralities and 95% highest density interval
Calculate Clustering Bayes Factors for when using the Stochastic Block...
Plot posterior complexity probabilities
Compare networks across groups using Bayesian inference
Fit a Bayesian analysis of networks
Edge evidence plot
Plot of interaction parameters and their 95% highest density intervals
Network plot
Print method for easybgm_compare objects
Print method for easybgm objects
Plot sensitivity to edge inclusion prior setting
Plot Posterior Structure Probabilities
Structure plot
Summary method for easybgm_compare objects
Summary method for easybgm objects
Fit and visualize the results of a Bayesian analysis of networks commonly found in psychology. The package supports fitting cross-sectional network models fitted using the packages 'BDgraph', 'bgms' and 'BGGM', as well as network comparison fitted using the 'bgms' and 'BBGM'. The package provides the parameter estimates, posterior inclusion probabilities, inclusion Bayes factor, and the posterior density of the parameters. In addition, for 'BDgraph' and 'bgms' it allows to assess the posterior structure space. Furthermore, the package comes with an extensive suite for visualizing results.