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Estimation of the Parameters in an Expanding Dynamic Network Model

Author

Listed:
  • Wei Zhao

    (North Carolina State University)

  • S.N. Lahiri

    (Washington University in St Louis)

Abstract

In this paper, we consider an expanding sparse dynamic network model where the time evolution is governed by a Markovian structure. Transition of the network from time t to t + 1 involves three components where a new node joins the existing network, some of the existing edges drop out, and new edges are formed with the incoming node. We consider long term behavior of the network density and establish its limit. We also study asymptotic distributions of the maximum likelihood estimators of key model parameters. We report results from a simulation study to investigate finite sample properties of the estimators.

Suggested Citation

  • Wei Zhao & S.N. Lahiri, 2022. "Estimation of the Parameters in an Expanding Dynamic Network Model," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 261-282, June.
    • Handle: RePEc:spr:sankha:v:84:y:2022:i:1:d:10.1007_s13171-021-00258-z
    DOI: 10.1007/s13171-021-00258-z
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    References listed on IDEAS

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