Accuracy criterion for mean field approximations of Markov processes on hypergraphs
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2022
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| _version_ | 1866917009323720704 |
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| author | Horvath, Illes Keliger, Daniel |
| author_facet | Horvath, Illes Keliger, Daniel |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2201_02041 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Accuracy criterion for mean field approximations of Markov processes on hypergraphs Horvath, Illes Keliger, Daniel Probability 60J28 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. |
| title | Accuracy criterion for mean field approximations of Markov processes on hypergraphs |
| topic | Probability 60J28 |
| url | https://arxiv.org/abs/2201.02041 |