brainGraph (version 1.0.0)

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.