net.barabasi.albert {fastnet} | R Documentation |
Barabasi-Albert Scale-free Graph
Description
Simulate a scale-free network using a preferential attachment mechanism (Barabasi and Albert, 1999)
Usage
net.barabasi.albert(n, m, ncores = detectCores(), d = FALSE)
Arguments
n |
Number of nodes of the network. |
m |
Number of nodes to which a new node connects at each iteration. |
ncores |
Number of cores, by default |
d |
A logical value determining whether the generated network is a directed or undirected (default) network. |
Details
Starting with m nodes, the preferential attachment mechaism adds one node and m edges in each step. The edges will be placed with one end on the newly-added node and the other end on the existing nodes, according to probabilities that associate with their current degrees.
Value
A list containing the nodes of the network and their respective neighbors.
Author(s)
Luis Castro, Xu Dong, Nazrul Shaikh.
References
Barabasi, A.- L. and Albert R. 1999. Emergence of scaling in random networks. Science, 286 509-512.
Examples
## Not run:
x <- net.barabasi.albert(1000, 20) # using default ncores
## End(Not run)