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Directed weighted random graphs with an increasing bi-degree sequence

Author

Listed:
  • Yong, Zhang
  • Chen, Siyu
  • Qin, Hong
  • Yan, Ting

Abstract

In this paper, we derive the consistency and asymptotic normality of the maximum likelihood estimator in the directed exponential random graph model with an increasing bi-degree sequence when the edges take finite discrete weight.

Suggested Citation

  • Yong, Zhang & Chen, Siyu & Qin, Hong & Yan, Ting, 2016. "Directed weighted random graphs with an increasing bi-degree sequence," Statistics & Probability Letters, Elsevier, vol. 119(C), pages 235-240.
    • Handle: RePEc:eee:stapro:v:119:y:2016:i:c:p:235-240
    DOI: 10.1016/j.spl.2016.08.007
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    References listed on IDEAS

    as
    1. Yan, Ting, 2015. "A note on asymptotic distributions in maximum entropy models for networks," Statistics & Probability Letters, Elsevier, vol. 98(C), pages 1-5.
    2. Yan, Ting & Zhao, Yunpeng & Qin, Hong, 2015. "Asymptotic normality in the maximum entropy models on graphs with an increasing number of parameters," Journal of Multivariate Analysis, Elsevier, vol. 133(C), pages 61-76.
    3. Ting Yan & Jinfeng Xu, 2013. "A central limit theorem in the β-model for undirected random graphs with a diverging number of vertices," Biometrika, Biometrika Trust, vol. 100(2), pages 519-524.
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    Cited by:

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    2. Mingli Chen & Kengo Kato & Chenlei Leng, 2021. "Analysis of networks via the sparse β‐model," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(5), pages 887-910, November.

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