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Dynamic Exponential Random Graph Model/Ushahidi
Rekodi ya ushahidi wa mbinu

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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Nukuu zimehamishwa kwa uhalisi kutoka kwa rekodi ya chanzo cha mbinu. Hakuna uthibitisho wa kiwango cha dai unaodokezwa kutoka kwao.

Dynamic Exponential Random Graph Model (Temporal ERGM)
Rekodi ya mbinu ya kiajenda · 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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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.

Hali ya ushahidi

Sources recorded, not reviewed

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

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