Parameter estimation in a dynamic Chung-Lu random graph

Fuente: arXiv
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Hauptverfasser: Hazra, Rajat Subhra, Mandjes, Michel, Wang, Jiesen
Format: Preprint
Veröffentlicht: 2025
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author Hazra, Rajat Subhra
Mandjes, Michel
Wang, Jiesen
author_facet Hazra, Rajat Subhra
Mandjes, Michel
Wang, Jiesen
contents In this paper we consider a dynamic version of the Chung-Lu random graph in which the edges alternate between being present and absent. The main contribution concerns a technique by which one can estimate the underlying dynamics from partial information, in particular from snapshots of the total number of edges present. The efficacy of our inference method is demonstrated through a series of numerical experiments.
format Preprint
id arxiv_https___arxiv_org_abs_2502_11613
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Parameter estimation in a dynamic Chung-Lu random graph
Hazra, Rajat Subhra
Mandjes, Michel
Wang, Jiesen
Probability
In this paper we consider a dynamic version of the Chung-Lu random graph in which the edges alternate between being present and absent. The main contribution concerns a technique by which one can estimate the underlying dynamics from partial information, in particular from snapshots of the total number of edges present. The efficacy of our inference method is demonstrated through a series of numerical experiments.
title Parameter estimation in a dynamic Chung-Lu random graph
topic Probability
url https://arxiv.org/abs/2502.11613