Random-Walk Models of Network Formation and Sequential Monte Carlo Methods for Graphs
网络形成的随机游走模型与图的序贯蒙特卡洛方法
Summary We introduce a class of generative network models that insert edges by connecting the starting and terminal vertices of a random walk on the network graph. Within the taxonomy of statistical network models, this class is distinguished by permitting the location of a new edge to depend explicitly on the structure of the graph, but being nonetheless statistically and computationally tractable. In the limit of infinite walk length, the model converges to an extension of…