For *n* nodes, sample a network with *nstim* stimuli and *cstim* combinatorial stimuli.

1 2 |

`n` |
Integer. Number of nodes. |

`nstim` |
Integer. Number of stimuli. |

`cstim` |
Integer. Number of combinatorial stimuli. |

`prop.inh` |
Proportion (in [0;1]) of the number of activating edges to be included as inhibiting edges in the network. |

`plot` |
Boolean. If TRUE, a plot of the generated graph is drawn. |

`gamma` |
Double. Strength of power law decay. Used for simulating the number of outgoing edges. |

`B` |
The prior edge probability matrix. |

`V` |
Vector of strings. Names of the nodes. |

`stimuli` |
List. See |

Simulates an artificial signalling network. Starts at *nstim* random stimuli and
selects random children, to which activation edges are drawn. These children are the new
stimuli and the procedure is repeated until all nodes were reached by activating edges.
Finally, *prop.inh*numedges* inhibiting edges are added randomly. The number of
stimuli combinations *cstim* is limited by *sum_{k=2}^n {k \choose n}*.
If defined, B gives a matrix containing prior probabilities for each possible edge in
the network.

List containing the adjacency list *phi* and the list of all stimuli.

Christian Bender

`simulatedata`

1 2 3 4 5 | ```
## Not run:
library(ddepn)
signalnetwork(n=10, nstim=4, cstim=4, prop.inh=.4, plot=TRUE)
## End(Not run)
``` |

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