weighted_richclub_w: The weighted rich-club effect
In tnet: Weighted, Two-Mode, and Longitudinal Networks Analysis

Description Usage Arguments Value Note Author(s) References Examples

This function calculates the weighted rich-club coefficient proposed in Opsahl, T., Colizza, V., Panzarasa, P., Ramasco, J.J., 2008. Prominence and control: The weighted rich-club effect. PRL 101.
http://toreopsahl.com/2008/12/12/article-prominence-and-control-the-weighted-rich-club-effect/

1 2	weighted_richclub_w(net, rich="k", reshuffle="weights", NR=1000, nbins=30, seed=NULL, directed=NULL)

`net`	A weighted edgelist
`rich`	specifies the richness parameter, either "k" or "s".
`reshuffle`	specifies the reshuffling procedure used, either "weights" or "links".
`NR`	number of random networks used.
`nbins`	the number of bins in the output
`seed`	the random generators seed, used to produce random yet reproducable results.
`directed`	logical parameter: whether the network is directed or undirected.

Returns a table with the fraction of phi(observed) over phi(null) for each k or s in the dataset.

version 1.0.0

Tore Opsahl; http://toreopsahl.com

Opsahl et al., 2008. Prominence and control: The weighted rich-club effect. PRL 101
http://toreopsahl.com/2008/12/12/article-prominence-and-control-the-weighted-rich-club-effect/

## Load sample data
sample <- cbind(
i=c(1,1,2,2,2,2,3,3,4,5),
j=c(2,3,1,3,4,5,1,2,2,2),
w=c(4,2,4,4,1,2,2,4,1,2))

## Run the function
weighted_richclub_w(sample, rich="k", reshuffle="weights", NR = 100)