small.world: Calculate graph small-worldness
In brainGraph: Graph Theory Analysis of Brain MRI Data

small.world

R Documentation

Calculate graph small-worldness

Description

small.world calculates the normalized characteristic path length and clustering coefficient based on observed and random graphs, used to calculate the small-world coefficient \sigma.

Usage

small.world(g.list, rand)

Arguments

`g.list`	A `brainGraphList` object or list of graphs
`rand`	List of (lists of) equivalent random graphs (output from `sim.rand.graph.par`)

Value

A data.table with the following components:

`density`	The range of density thresholds used.
`N`	The number of random graphs that were generated.
`Lp`, `Lp.rand`, `Lp.norm`	The observed, average random, and normalized characteristic path length.
`Cp`, `Cp.rand`, `Cp.norm`	The observed, average random, and normalized clustering coefficient.
`sigma`	The small-world measure of the graph.

Author(s)

Christopher G. Watson, cgwatson@bu.edu

References

Watts, D.J. and Strogatz S.H. (1998) Collective dynamics of "small-world" networks. Nature, 393, 440–442. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1038/30918")}

brainGraph documentation built on June 22, 2024, 7:36 p.m.