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可交换随机图中异常边的极限行为

Limiting behavior of anomalous edges in exchangeable random graphs

  • 摘要: 社区结构是许多社交网络的共同特征。不同社区之间的边称为异常边。根据给定的一个两社区网络,我们通过假定顶点所属的社区具有可交换性来生成随机图。当图的大小趋于无穷大时,在正则条件下本文建立了随机图中异常边数量的渐近正态性,方法是基于随机单调性且将弱收敛转化为条件弱收敛。

     

    Abstract: Community structures are a common feature of many social networks. Anomalous edges are those edges that fall between distinct communities. According to a given network with two communities, random graphs are generated by assuming that the communities of vertices are exchangeable. In this paper, under some restriction conditions, the asymptotic normality of the number of anomalous edges in such random graphs is established as the graph size tends to infinity, where the method of transforming weak convergence into conditional weak convergence on the basis of stochastic monotonicity is utilized.

     

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