grow_hk: Holme and Kim (2002) network growth model

In memnet: Network Tools for Memory Research

Description

Grow networks using Holme & Kim's (2002) model, which combines preferential attachment with tunable triad formation flexibly controlling the amount of clustering in the network via p.

Usage

grow_hk(n = 100L, m = 5L, p = 5)

Arguments

n	Integer. Number of nodes in the network.
m	Integer. Number of edges added for each incoming node.
p	Numeric. Proability that a triad formation step follows a preferential attachment step.

Value

n x n adjacency matrix.

References

Holme, P., & Kim, B. J. (2002). Growing scale-free networks with tunable clustering. Physical review E, 65(2), 026107.

Examples

# generate small graph
grow_hk(n = 6, m = 2, p = .1)

## Not run: 
# generate large graph, low clustering
grow_hk(n = 100, m = 10, p = .1)

# generate large graph, high clustering
grow_hk(n = 100, m = 10, p = .9)

## End(Not run)

memnet documentation built on May 2, 2019, 9:35 a.m.