ERGM
Exponential-Family Random Graph Models
$$P(y) = h(y) \exp\{\eta(\theta) \cdot s(y)\} / \kappa(\theta)$$
Most of my work is done in the powerful exponential-family random graph model (ERGM) framework. This class of models supports:
- a wide variety of network features and structures,
- extensions for modelling network evolution, and
- inference from minimal samples,
at the cost of being
Related packages
ergm: Fit, Simulate and Diagnose Exponential-Family Models for Networks
ergm.multi: Fit, Simulate and Diagnose Exponential-Family Models for Multiple or Multilayer Networks
ergm.count: Fit, Simulate and Diagnose Exponential-Family Models for Networks with Count Edges
ergm.rank: Fit, Simulate and Diagnose Exponential-Family Models for Rank-Order Relational Data
tergm: Fit, Simulate and Diagnose Models for Network Evolution Based on Exponential-Family Random Graph Models