| post_processing_rgm {rgm} | R Documentation |
Post-Processing for RGM (Random Graph Model)
Description
This function performs post-processing on simulated data and results from a Random Graph Model (RGM). It calculates mean posterior estimates, compares true and estimated edge probabilities, generates various diagnostic plots, and returns a list of these plots.
Usage
post_processing_rgm(simulated_data, results)
Arguments
simulated_data |
A list containing simulated data from an RGM. |
results |
A list containing results from fitting an RGM to 'simulated_data'. |
Value
A list containing ggplot objects for different diagnostics: - 'rgm_recovery': A plot comparing true and estimated probit values. - 'estimation_of_alpha': A plot comparing true and estimated alpha values. - 'posterior_distribution': A density plot of the posterior distribution of the beta parameter. - 'beta_convergence': A trace plot of the beta parameter across MCMC iterations. - 'roc_plot': A ROC plot for graph recovery performance. - 'edge_prob': A heatmap of posterior edge probabilities for each environment.