Description Usage Arguments Details Value Author(s) References See Also Examples

Generates a small-world random graph.

1 2 |

`n` |
Integer scalar. Set the size of the graph. |

`k` |
Integer scalar. Set the initial degree of the ring (must be less than |

`p` |
Numeric scalar/vector of length |

`both.ends` |
Logical scalar. When |

`self` |
Logical scalar. When |

`multiple` |
Logical scalar. When |

`undirected` |
Logical scalar. Passed to |

Implemented as in Watts and Strogatz (1998). Starts from an
undirected ring with *n* vertices all with degree *k* (so it must
be an even number), and then rewire each edge by setting the endpoint (so
now you treat it as a digraph) randomly any vertex in *N \ {i}*
avoiding multiple links (by default) using the rewiring algorithm described on
the paper.

A random graph of size *n*n* following the small-world
model. The resulting graph will have `attr(graph, "undirected")=FALSE`

.

George G. Vega Yon

Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of "small-world" networks. Nature, 393(6684), 440–2. http://dx.doi.org/10.1038/30918

Newman, M. E. J. (2003). The Structure and Function of Complex Networks. SIAM Review, 45(2), 167–256. http://doi.org/10.1137/S003614450342480

Other simulation functions: `permute_graph`

,
`rdiffnet`

, `rewire_graph`

,
`rgraph_ba`

, `rgraph_er`

,
`ring_lattice`

1 2 3 4 5 6 7 8 9 10 11 12 | ```
library(igraph)
set.seed(7123)
x0 <- graph_from_adjacency_matrix(rgraph_ws(10,2, 0))
x1 <- graph_from_adjacency_matrix(rgraph_ws(10,2, .3))
x2 <- graph_from_adjacency_matrix(rgraph_ws(10,2, 1))
oldpar <- par(no.readonly=TRUE)
par(mfrow=c(1,3))
plot(x0, layout=layout_in_circle, edge.curved=TRUE, main="Regular")
plot(x1, layout=layout_in_circle, edge.curved=TRUE, main="Small-world")
plot(x2, layout=layout_in_circle, edge.curved=TRUE, main="Random")
par(oldpar)
``` |

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