A cluster expansion approach to exponential random graph models

被引:2
作者
Yin, Mei [1 ]
机构
[1] Univ Texas Austin, Dept Math, Austin, TX 78712 USA
来源
JOURNAL OF STATISTICAL MECHANICS-THEORY AND EXPERIMENT | 2012年
关键词
series expansions; exact results; random graphs; networks; PHASE-TRANSITION; NETWORK;
D O I
10.1088/1742-5468/2012/05/P05004
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
The exponential family of random graphs are among the most widely studied network models. We show that any exponential random graph model may alternatively be viewed as a lattice gas model with a finite Banach space norm. The system may then be treated using cluster expansion methods from statistical mechanics. In particular, we derive a convergent power series expansion for the limiting free energy in the case of small parameters. Since the free energy is the generating function for the expectations of other random variables, this characterizes the structure and behavior of the limiting network in this parameter region.
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页数:15
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