This function will simulate N simple random graphs with the same clustering
and degree sequence as the input. Essentially a wrapper for
`sim.rand.graph.clust`

and
`set.brainGraph.attributes`

. It uses
`foreach`

to speed it up. If you do not want to match by
clustering, then it will do a simple rewiring of the given graph (the number
of rewire's equaling the larger of 1e4 and 10 * number of edges).

1 | ```
sim.rand.graph.par(g, N, clustering = TRUE, ...)
``` |

`g` |
A graph with the characteristics for simulation of random graphs |

`N` |
The number of iterations |

`clustering` |
Logical for whether or not to control for clustering |

`...` |
Other parameters (passed to |

A list of *N* random graphs with vertex and graph attributes.

`sim.rand.graph.clust, rewire`

1 2 3 4 5 | ```
## Not run:
rand1 <- sim.rand.graph.par(g1[[N]], N=1e3, clustering=F)
rand1.cl <- sim.rand.graph.par(g1[[N]], N=1e2, max.iters=1e3)
## End(Not run)
``` |

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