Generating uniformly distributed random networks
Abstract
The analysis of real networks taken from the biological, social, and physical sciences often requires a carefully posed statistical null-hypothesis approach. One common method requires comparing real networks to an ensemble of random matrices that satisfy realistic constraints in which each different matrix member is equiprobable. We discuss existing methods for generating uniformly distributed (constrained) random matrices, describe their shortcomings, and present an efficient technique that should have many practical applications.
- Publication:
-
Physical Review E
- Pub Date:
- November 2005
- DOI:
- 10.1103/PhysRevE.72.056708
- Bibcode:
- 2005PhRvE..72e6708A
- Keywords:
-
- 02.70.-c;
- 89.75.Hc;
- 89.75.Fb;
- 05.45.-a;
- Computational techniques;
- simulations;
- Networks and genealogical trees;
- Structures and organization in complex systems;
- Nonlinear dynamics and chaos