robustness: Analysis of network robustness
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
}
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.
}
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.
}
author{
Christopher G. Watson, email{cgwatson@bu.edu}
}
references{
Albert R., Jeong H., Barabasi A. (2000) emph{Error and attack
tolerance of complex networks}. Nature, 406:378-381.
}