Description Usage Arguments Value See Also Examples

Given a *(K\times K)* stochastic blockmodel W, `gmodel.block`

generates an (n-by-n) binary random graphs. All K blocks have
same number of nodes, or almost identical if n is not a multiple
of K. Parameter `noloop`

controls whether generated observations
have an edge from a node to itself, called a loop.

1 | ```
gmodel.block(W, n, rep = 1, noloop = TRUE)
``` |

`W` |
a |

`n` |
the number of nodes for each observation. |

`rep` |
the number of observations to be generated. |

`noloop` |
a logical value; TRUE for graphs without self-loops, FALSE otherwise. |

a named list containing

- G
depending on

`rep`

value,- (rep=1)
an

*(n\times n)*observation, or- (rep>1)
a length-

`rep`

list where each element is an observation is an*(n\times n)*realization from the model.

- P
an

*(n\times n)*probability matrix of generating each edge.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ```
## Not run:
## set inputs
W = matrix(c(0.9,0.2,0.2,0.7),nr=2)
n = 200
## generate 2 observations without self-loops.
out <- gmodel.block(W,n,rep=2,noloop=TRUE)
## Visualize generated graphs
par(mfrow=c(1,2))
image(out$G[[1]]); title("Observation 1")
image(out$G[[2]]); title("Observation 2")
## End(Not run)
``` |

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