Artzy-Randrup Yael, Stone Lewi
Biomathematics Unit, Faculty of Life Sciences, Tel Aviv University, Ramat Aviv 69978, Israel.
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Nov;72(5 Pt 2):056708. doi: 10.1103/PhysRevE.72.056708. Epub 2005 Nov 16.
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.
对取自生物、社会和物理科学的真实网络进行分析，通常需要采用精心构建的统计零假设方法。一种常见方法是将真实网络与一组满足现实约束条件的随机矩阵进行比较，其中每个不同的矩阵成员具有同等的可能性。我们讨论了生成均匀分布（受约束）随机矩阵的现有方法，描述了它们的缺点，并提出了一种应具有许多实际应用的有效技术。
