brainGraph (version 0.48.0)

small.world: Calculate graph small-worldness

Description

This function will calculate the characteristic path length and clustering coefficient, which are used to calculate small-worldness.

Usage

small.world(g, rand)

Arguments

g

The graph (or list of graphs) of interest

rand

List of (lists of) equivalent random graphs (output from sim.rand.graph.par)

Value

• A data frame with the following components:
• density
  The range of density thresholds used.
• N
  The number of random graphs that were generated.
• Lp
  The characteristic path length.
• Cp
  The clustering coefficient.
• Lp.rand
  The mean characteristic path length of the random graphs with the same degree distribution as g.
• Cp.rand
  The mean clustering coefficient of the random graphs with the same degree distribution as g.
• Lp.norm
  The normalized characteristic path length.
• Cp.norm
  The normalized clustering coefficient.
• sigma
  The small-world measure of the graph.

References

Watts D.J., Strogatz S.H. (1998) Collective dynamics of 'small-world' networks. Nature, 393:440-442.