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    Parameter estimation in a dynamic Chung-Lu random graph

    Rajat Subhra Hazra and Michel Mandjes*

    Jiesen Wang

    • *Also at Korteweg-de Vries Institute for Mathematics, University of Amsterdam, The Netherlands.

    Phys. Rev. E 112, 014315 – Published 25 July, 2025

    DOI: https://doi.org/10.1103/6w2h-p1sr

    Abstract

    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.

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