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Computes the area under the robustness curve using trapezoidal integration. Higher AUC indicates a more robust network. Maximum AUC is 1.0.

Usage

robustness_auc(x)

Arguments

x

A robustness result from robustness.

Value

Numeric AUC value between 0 and 1.

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