| weighted_richclub_tm {tnet} | R Documentation |
The weighted rich-club effect (two-mode networks)
Description
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. It incorporates two extentions explained in this blog post http://toreopsahl.com/2009/05/29/weighted-rich-club-effect-a-more-appropriate-null-model-for-scientific-collaboration-networks/:
1) a new way of reshuffling (two-mode link reshuffling;
2) calculating significance levels if there are more than 100 random networks (see my PhD thesis; http://toreopsahl.com/publications/thesis/)
Usage
weighted_richclub_tm(net, NR=1000, seed=NULL, projection.method="Newman", nbins=30)Arguments
net |
A binary two-mode edgelist |
NR |
number of random networks used. |
seed |
the random generators seed, used to produce random yet reproducable results. |
projection.method |
the method used to project the two-mode network to a weighted one-mode network: either "sum" or "Newman" |
nbins |
the number of bins in the output |
Value
Returns a table with the fraction of phi(observed) over phi(null). Nbins controls the number of rows.
Note
version 1.0.0
Author(s)
Tore Opsahl; http://toreopsahl.com
References
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/
http://toreopsahl.com/2009/05/29/weighted-rich-club-effect-a-more-appropriate-null-model-for-scientific-collaboration-networks/
Examples
## Load data
data(tnet)
## Run the function on a subset
weighted_richclub_tm(Newman.Condmat.95.99.net.2mode[1:100,], NR=10)