You can make random uniform directed hypergraphs

Yanna Kraakman*, Clara Stegehuis

*Corresponding author for this work

Research output: Contribution to conferencePosterAcademic

37 Downloads (Pure)

Abstract

Directed hypergraphs (DHs) capture higher-order, directed interactions. Uniformly sampled random DHs can serve as a null model: Structures that appear more often in your network than in the null model, could be significant. We introduce configuration models for DHs, in which the vertex and arc degrees are fixed, and the connections are randomized. We then sample from those with a Markov chain Monte Carlo method, involving arc swaps. For 8 types of DHs (with/without self-loops, degenerate arcs, double arcs), we (dis)prove uniformity of this sampling method.
Original languageEnglish
Publication statusIn preparation - 2023
Event21st INFORMS Applied Probability Society Conference 2023 - Centre de Congres Prouve, Nancy, France
Duration: 28 Jun 202330 Jun 2023
Conference number: 21
https://informs-aps2023.event.univ-lorraine.fr/

Conference

Conference21st INFORMS Applied Probability Society Conference 2023
Country/TerritoryFrance
CityNancy
Period28/06/2330/06/23
Internet address

Keywords

  • Directed Hypergraphs
  • Configuration Model
  • Markov chain Monte Carlo
  • Uniform sampling

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