robustness: Analysis of network robustness

Description Usage Arguments Details Value Author(s) References

View source: R/robustness.R

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

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

Arguments

g

An igraph graph object

type

Character string; either 'vertex' or 'edge' removals (default: vertex)

measure

Character string; sort by either 'btwn.cent' or 'degree', or choose 'random' (default: btwn.cent)

N

Integer; the number of iterations if random is chosen (default: 1e3)

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.

Value

Numeric vector representing the ratio of maximal component size after each removal to the observed graph's maximal component size

Author(s)

Christopher G. Watson, [email protected]

References

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


brainGraph documentation built on May 29, 2018, 9:03 a.m.