Constrained Randomisation of Weighted Networks

Details Constrained Randomisation of Weighted Networks Constrained Randomisation of Weighted Networks

2012-01-03

arxiv.org/abs/1201.0638v1

Physical Review E 84, 026103 (2011)

Physics

Data Analysis, Statistics and Probability

11 pages, 5 figures

Scientific paper

10.1103/PhysRevE.84.026103

We propose a Markov chain method to efficiently generate 'surrogate networks' that are random under the constraint of given vertex strengths. With these strength-preserving surrogates and with edge-weight-preserving surrogates we investigate the clustering coefficient and the average shortest path length of functional networks of the human brain as well as of the International Trade Networks. We demonstrate that surrogate networks can provide additional information about network-specific characteristics and thus help interpreting empirical weighted networks.

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