Generalised hypergeometric ensembles of random graphs: The configuration model as an urn problem

Abstract

We introduce a broad class of random graph models: the generalised hypergeometric ensemble (GHypEG). This class enables to solve some long-standing problems in random graph theory. First, GHypEG provides an elegant and compact formulation of the well-known configuration model in terms of an urn problem. Second, GHypEG allows incorporating arbitrary tendencies to connect different vertex pairs. Third, we present the closed-form expressions of the associated probability distribution ensures the analytical tractability of our formulation. This is in stark contrast with the previous state-of-the-art, which is to implement the configuration model by means of computationally expensive procedures.