Constrained Randomisation of Weighted Networks

نویسندگان

  • Gerrit Ansmann
  • Klaus Lehnertz
چکیده

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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عنوان ژورنال:
  • Physical review. E, Statistical, nonlinear, and soft matter physics

دوره 84 2 Pt 2  شماره 

صفحات  -

تاریخ انتشار 2011