EDGE EXCHANGEABLE MODELS FOR INTERACTION NETWORKS.

ABSTRACT: Many modern network datasets arise from processes of interactions in a population, such as phone calls, email exchanges, co-authorships, and professional collaborations. In such interaction networks, the edges comprise the fundamental statistical units, making a framework for edge-labeled networks more appropriate for statistical analysis. In this context we initiate the study of edge exchangeable network models and explore its basic statistical properties. Several theoretical and practical features make edge exchangeable models better suited to many applications in network analysis than more common vertex-centric approaches. In particular, edge exchangeable models allow for sparse structure and power law degree distributions, both of which are widely observed empirical properties t

SUBMITTER: Crane H 

PROVIDER: S-EPMC6241523 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature