Accuracy criterion for mean field approximations of Markov processes on hypergraphs

Dániel Keliger and Illés Horváth

Physica A: Statistical Mechanics and its Applications, 2023, vol. 609, issue C

Abstract: We provide error bounds for the N-intertwined mean-field approximation (NIMFA) for local density-dependent Markov population processes with a well-distributed underlying network structure showing NIMFA being accurate when a typical vertex has many neighbors. The result justifies some of the most common approximations used in epidemiology, statistical physics and opinion dynamics literature under certain conditions. We allow interactions between more than 2 individuals, and an underlying hypergraph structure accordingly.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:609:y:2023:i:c:s0378437122009281

DOI: 10.1016/j.physa.2022.128370

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