Computes the area under the robustness curve using trapezoidal integration. Higher AUC indicates a more robust network. Maximum AUC is 1.0.
Arguments
- x
A robustness result from
robustness.
Examples
if (requireNamespace("igraph", quietly = TRUE)) {
g <- igraph::sample_pa(30, m = 2, directed = FALSE)
rob_btw <- robustness(g, measure = "betweenness")
rob_rnd <- robustness(g, measure = "random", n_iter = 20)
cat("Betweenness attack AUC:", round(robustness_auc(rob_btw), 3), "\n")
cat("Random failure AUC:", round(robustness_auc(rob_rnd), 3), "\n")
}
#> Betweenness attack AUC: 0.196
#> Random failure AUC: 0.434
