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Weighted Exponential Random Graph Model/Evidence
Method evidence record

Weighted Exponential Random Graph Model

The Weighted Exponential Random Graph Model (W-ERGM) extends the classic binary ERGM framework to networks whose edges carry quantitative values — such as frequency of contact, trade volume, or collaboration intensity. It models the entire valued-edge network as a probability distribution defined over all possible weighted graphs, enabling researchers to test whether structural patterns such as reciprocity, transitivity, or degree distribution arise beyond what chance alone would produce.

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Source record

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

Weighted Exponential Random Graph Model (Valued-Edge ERGM)
Taxonomic method record · ml-model / network-analysis
  • Krivitsky, P. N. (2012). Exponential-family random graph models for valued networks. Electronic Journal of Statistics, 6, 1100–1128. · DOI 10.1214/12-EJS696
  • Robins, G., Pattison, P., Kalish, Y., & Lusher, D. (2007). An introduction to exponential random graph (p*) models for social networks. Social Networks, 29(2), 173–191. · DOI 10.1016/j.socnet.2006.08.002
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Curated claims

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Related methods

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

Taxonomic bucketWeighted Degree Centralitymachine-suggested · Relational suggestion, not evidence.Taxonomic bucketWeighted Modularity Analysismachine-suggested · Relational suggestion, not evidence.Taxonomic bucketWeighted Social Network Analysismachine-suggested · Relational suggestion, not evidence.Taxonomic bucketWeighted Stochastic Block Modelmachine-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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