Generalised hypergeometric ensembles of random graphs: the configuration model as an urn problem
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Abstract (arXiv)
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 to incorporate 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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Oct 2018.
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2 papers.