Machine learningNetwork science
动态指数随机图模型
动态指数随机图模型（TERGM / STERGM）将经典的ERGM框架扩展到面板网络数据，模拟网络关系如何随时间形成和溶解，其模式取决于结构倾向、节点属性和网络自身过去的状况。它为纵向网络变化提供了统计学上合理的推断。
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来源
- 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 ↗
如何引用本页
ScholarGate. (2026, June 3). Dynamic Exponential Random Graph Model (Temporal ERGM). ScholarGate. https://scholargate.app/zh/network-analysis/dynamic-exponential-random-graph-model
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