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Dynamic Exponential Random Graph Model/Evidence
Method evidence record

Dynamic Exponential Random Graph Model

The Dynamic Exponential Random Graph Model (TERGM / STERGM) extends the classic ERGM framework to panel network data, modeling how a network's ties form and dissolve over time as a function of structural tendencies, nodal attributes, and the network's own past state. It provides statistically principled inference about longitudinal network change.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Dynamic Exponential Random Graph Model (Temporal ERGM)
Taxonomic method record · ml-model / network-analysis
  • Hanneke, S., Fu, W., & Xing, E. P. (2010). Discrete temporal models of social networks. Electronic Journal of Statistics, 4, 585–605. · DOI 10.1214/09-EJS548
  • Krivitsky, P. N., & Handcock, M. S. (2014). A separable model for dynamic networks. Journal of the Royal Statistical Society: Series B, 76(1), 29–46. · DOI 10.1111/rssb.12014
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketDynamic Stochastic Block Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketNetwork Diffusion Analysismachine-suggested · Relational suggestion, not evidence.Used in the same domainStochastic Block Modelmachine-suggested · Relational suggestion, not evidence.Used in the same domainTemporal Network Analysismachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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