# Comparing a sub network to the randomly simulated ones

### Description

Comparing a sub network with randomly simulated ones from the whole network.

### Usage

1 2 3 |

### Arguments

`subgraph` |
An igraph object. |

`graph` |
An igraph object. The whole one for random simulation. |

`nsim` |
Times for simulation. Default value is |

`degree` |
Logical value, indicating whether to do vertex degree comparing (if |

`betweenness` |
Logical value, indicating whether to do betweenness comparing (if |

`ave.path.len` |
Logical value, indicating whether to do average path comparing (if |

`eccentricity` |
Logical value, indicating whether to do eccentricity comparing (if |

`cc` |
Logical value, indicating whether to do clustering coefficient comparing (if |

`method` |
Test method, currently only |

`FDR` |
False discovery rate. Default value is |

### Value

A matrix of compared parameters and plots.

### References

Y Benjamini, Y Hochberg. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological), Vol. 57, No. 1. (1995), pp. 289-300.

### See Also

`net.comparing`

, `comp.subnet`

### Examples

1 2 3 4 | ```
g<-barabasi.game(100,power=0.8,directed=FALSE)
subg<-induced.subgraph(g,sample(1:100,30))
comp.rand.subnet(subg,g)
comp.rand.subnet(subg,g,degree=TRUE)
``` |