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Statistical Inference for Valued-Edge Networks: The Generalized Exponential Random Graph Model

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  • Bruce A Desmarais
  • Skyler J Cranmer

Abstract

Across the sciences, the statistical analysis of networks is central to the production of knowledge on relational phenomena. Because of their ability to model the structural generation of networks based on both endogenous and exogenous factors, exponential random graph models are a ubiquitous means of analysis. However, they are limited by an inability to model networks with valued edges. We address this problem by introducing a class of generalized exponential random graph models capable of modeling networks whose edges have continuous values (bounded or unbounded), thus greatly expanding the scope of networks applied researchers can subject to statistical analysis.

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  • Bruce A Desmarais & Skyler J Cranmer, 2012. "Statistical Inference for Valued-Edge Networks: The Generalized Exponential Random Graph Model," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-12, January.
    • Handle: RePEc:plo:pone00:0030136
    DOI: 10.1371/journal.pone.0030136
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    2. Etsuji Suzuki & Eiji Yamamoto & Soshi Takao & Ichiro Kawachi & S V Subramanian, 2012. "Clarifying the Use of Aggregated Exposures in Multilevel Models: Self-Included vs. Self-Excluded Measures," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-9, December.
    3. Peter R. Herman, 2022. "Modeling complex network patterns in international trade," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 158(1), pages 127-179, February.
    4. Neal, Zachary & Domagalski, Rachel & Yan, Xiaoqin, 2020. "Party Control as a Context for Homophily in Collaborations among US House Representatives, 1981 -- 2015," OSF Preprints qwdxs, Center for Open Science.
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    6. Scott W. Duxbury, 2023. "The Problem of Scaling in Exponential Random Graph Models," Sociological Methods & Research, , vol. 52(2), pages 764-802, May.
    7. Lee, Jihui & Li, Gen & Wilson, James D., 2020. "Varying-coefficient models for dynamic networks," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
    8. Duxbury, Scott W, 2019. "Mediation and Moderation in Statistical Network Models," SocArXiv 9bs4u, Center for Open Science.
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