ProNet (version 1.0.0)

comp.rand.subnet: Comparing a sub network to the randomly simulated ones

Description

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

Usage

comp.rand.subnet(subgraph, graph, nsim = 1000, degree = FALSE, betweenness = FALSE, ave.path.len = FALSE, eccentricity = FALSE, cc = FALSE, method = "utest", FDR = 0.05)

Arguments

subgraph

An igraph object.

graph

An igraph object. The whole one for random simulation.

nsim

Times for simulation. Default value is 1000.

degree

Logical value, indicating whether to do vertex degree comparing (if TRUE) or not (if FALSE).

betweenness

Logical value, indicating whether to do betweenness comparing (if TRUE) or not (if FALSE).

ave.path.len

Logical value, indicating whether to do average path comparing (if TRUE) or not (if FALSE).

eccentricity

Logical value, indicating whether to do eccentricity comparing (if TRUE) or not (if FALSE).

cc

Logical value, indicating whether to do clustering coefficient comparing (if TRUE) or not (if FALSE).

method

Test method, currently only utest is supported.

FDR

False discovery rate. Default value is 0.05.

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

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)