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Event history analysis of dynamic networks

Author

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  • T Sit
  • Z Ying
  • Y Yu

Abstract

SummaryStatistical analysis on networks has received growing attention due to demand from various emerging applications. In dynamic networks, one of the key interests is to model the event history of time-stamped interactions among nodes. We model dynamic directed networks via multivariate counting processes. A pseudo partial likelihood approach is exploited to capture the network dependence structure. Asymptotic results are established. Numerical experiments are performed to demonstrate the effectiveness of our proposal.

Suggested Citation

  • T Sit & Z Ying & Y Yu, 2021. "Event history analysis of dynamic networks," Biometrika, Biometrika Trust, vol. 108(1), pages 223-230.
    • Handle: RePEc:oup:biomet:v:108:y:2021:i:1:p:223-230.
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    File URL: http://hdl.handle.net/10.1093/biomet/asaa045
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    Cited by:

    1. Long, Yuhang & Huang, Tao, 2022. "A note on a dynamic network model with homogeneous structure," Statistics & Probability Letters, Elsevier, vol. 184(C).

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