degclust: Compute degree and clustering for small complex networks

In krehfeld/nest: Non-equally spaced time series analysis

Description

Compute degree and clustering for small complex networks. For time-ordered nodes, the network measures are computed irrespectively of the time (total), in forward, and backward sense.

Usage

degclust(A)

Arguments

A	Adjacency matrix. diag(A) should be zero (no self-loops).

Value

A list of

degree	A list of forward,backward, and total degree
clustering	A list of forward,backward, and total local clustering

Author(s)

Kira Rehfeld

References

Watts, D.J. & Strogatz S. (1998) Collective dynamics of small-world networks, Nature 393 (1998), doi:10.1038/30918 Rehfeld, K. , Molkenthin, N. and Kurths, J. (2014) Testing the detectability of spatio-temporal climate transitions from paleoclimate networks with the START model, Nonlinear Processes in Geophysics, 21 (3), pp. 691-703. doi:10.5194/npg-21-691-2014

Examples

A<-matrix(1,nrow=4,ncol=4); diag(A)=0;
degclust(A)$degree$tot
degclust(A)$clustering$tot
A[3,4]=A[4,3]=0
degclust(A)$clustering$tot

krehfeld/nest documentation built on May 28, 2019, 12:33 a.m.