brainGraph (version 1.0.0)

robustness: Analysis of network robustness

Description

This function performs a "targeted attack" of a graph or a "random failure" analysis, calculating the size of the largest component after edge or vertex removal.

Usage

robustness(g, type = c("vertex", "edge"), measure = c("btwn.cent", "degree",
  "random"), N = 1000)

Arguments

g

The igraph graph object of interest

type

A character string; either 'vertex' or 'edge' removals

measure

A character string; sort by either 'btwn.cent' or 'degree', or choose 'random'

N

Integer; the number of iterations if random is chosen

Value

A vector representing the ratio of maximal component size after each removal to the graph's original maximal component

Details

In a targeted attack, it will sort the vertices by either degree or betweenness centrality (or sort edges by betweenness), and successively remove the top vertices/edges. Then it calculates the size of the largest component. In a random failure analysis, vertices/edges are removed in a random order.

References

Albert R., Jeong H., Barabasi A. (2000) Error and attack tolerance of complex networks. Nature, 406:378-381.