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Statistical properties of a generalized threshold network model

机译:广义阈值网络模型的统计性质

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摘要

The threshold network model is a type of finite random graph. In this paper, we introduce a generalized threshold network model. A pair of vertices with random weights is connected by an edge when real-valued functions of the pair of weights belong to given Borel sets. We extend several known limit theorems for the number of prescribed subgraphs and prove a uniform strong law of large numbers. We also prove two limit theorems for the local and global clustering coefficients.
机译:阈值网络模型是一种有限随机图。在本文中,我们介绍了广义阈值网络模型。当一对权重的实值函数属于给定的Borel集时,一对具有随机权重的顶点通过一条边连接。我们针对规定的子图的数量扩展了几个已知的极限定理,并证明了一个统一的强大的大数定律。我们还证明了局部和全局聚类系数的两个极限定理。

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