How might one test the hypothesis that graphs were sampled from the same distribution? Here, we compare two statistical tests that address this question. The first uses the observed subgraph densities themselves as estimates of those of the underlying distribution. The second test uses a new approach that converts these subgraph densities into estimates of the graph cumulants of the distribution. We demonstrate -- via theory, simulation, and application to real data -- the superior statistical power of using graph cumulants.

翻译：如何检验从相同分布图中抽样的假设?在这里,我们比较两个统计测试来解决这个问题。第一个测试使用观测到的子集密度本身作为基本分布的估计数。第二个测试使用一种新的方法将这些子集密度转换成分布图积积的估计数。我们通过理论、模拟和对真实数据的应用,展示了使用图形积聚剂的优越统计能力。