Machine learningNetwork science

Directed Exponential Random Graph Model

The Directed Exponential Random Graph Model (Directed ERGM) is a family of statistical models for directed networks that estimates the probability of observing a given directed graph as a function of structural configurations — such as reciprocity, transitive triads, and in-degree centralization — and node or dyad covariates, enabling principled inference about the social processes that generate directed ties.

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Sources

  1. 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
  2. Frank, O. & Strauss, D. (1986). Markov graphs. Journal of the American Statistical Association, 81(395), 832-842. DOI: 10.2307/2289017

Related methods

ScholarGateDirected Exponential Random Graph Model (Directed Exponential Random Graph Model (Directed ERGM / p* Model for Directed Networks)). Retrieved 2026-06-04 from https://scholargate.app/tr/network-analysis/directed-exponential-random-graph-model