In this paper, we explore the two-star Exponential Random Graph Model, which is a two parameter exponential family on the space of simple labeled graphs. We introduce auxiliary variables to express the two-star model as a mixture of the $\beta$ model on networks. Using this representation, we study asymptotic distribution of the number of edges, and the sampling variance of the degrees. In particular, the limiting distribution for the number of edges has similar phase transition behavior to that of the magnetization in the Curie-Weiss Ising model of Statistical Physics. Using this, we show existence of consistent estimates for both parameters in all parameter domains. Finally, we prove that the centered partial sum of degrees converges as a process to a Brownian bridge in all parameter domains, irrespective of the phase transition.
翻译:在本文中,我们探索了两星指数随机图模型,这是简单标签图表空间上的两个参数指数系。我们引入了辅助变量,将两星模型作为网络$\beta$模型的混合体来表达。我们使用这个表示法,研究边缘数的无症状分布,以及不同度的抽样差异。特别是,边缘数的有限分布与Curie-Weiss Ising统计物理模型中的磁化相类似的阶段过渡行为。我们使用这个参数,就所有参数领域两个参数提供了一致的估计。最后,我们证明,所有参数区域中位数的部分总和是布朗桥的一个过程,而不论阶段过渡如何。