Sharp Threshold for the Frechet Mean (or Median) of Inhomogeneous Erdos-Renyi Random Graphs
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Abstract (arXiv)
We address the following foundational question: what is the population, and sample, Frechet mean (or median) graph of an ensemble of inhomogeneous Erdos-Renyi random graphs? We prove that if we use the Hamming distance to compute distances between graphs, then the Frechet mean (or median) graph of an ensemble of inhomogeneous random graphs is obtained by thresholding the expected adjacency matrix of the ensemble. We show that the result also holds for the sample mean (or median) when the population expected adjacency matrix is replaced with the sample mean adjacency matrix. Consequently, the Frechet mean (or median) graph of inhomogeneous Erdos-Renyi random graphs exhibits a sharp threshold: it is either the empty graph, or the complete graph. This novel theoretical result has some significant practical consequences; for instance, the Frechet mean of an ensemble of sparse inhomogeneous random graphs is always the empty graph.
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References · 5
- 2017Community Detection and Stochastic Block Modelscited by 317
- 2016Community detection in networks: A user guidecited by 105
- 2014Hypothesis Testing For Network Data in Functional Neuroimagingcited by 20
- 2019Modeling Network Populations via Graph Distancescited by 13
- 2021Network Recovery from Unlabeled Noisy Samplescited by 5
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