This is a plot function to determine whether the distributions of predictions from ERGM and FERGM objects differ. It does so by using a Kolmogorov-Smirnov Test.
Matrix of correctly predicted ties produced by the
The significance level that should be used for the test.
ks.test output to determine if the percent of correctly predicted ERGM ties are less than those of the FERGM and prints a message to assist with interpretation
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# load example data data("ergm.fit") data("fergm.fit") data("mesa") # Use built in compare_predictions function to compare predictions of ERGM and FERGM, # few replications due to example predict_out <- compare_predictions(ergm.fit = ergm.fit, fergm.fit = fergm.fit, net = mesa, replications = 10, seed = 12345) # We can also conduct a KS test to determine if the FERGM fit it statistically # distinguishable from the ERGM fit compare_predictions_test(predict_out)
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