Simulate Dynamic Networks using Exponential Random Graph Models (ERGM) Family
binaryPlot
clustCoef
dnr: A package for simulating dynamic networks using ERGM family model...
Implementation of simulation engine for dynamic networks using smoothi...
Implementation of simulation engine for dynamic networks using smoothi...
Implementation of simulation engine for dynamic networks without using...
Simulation Engine for dynamic Vertex case.
Simulation Engine for dynamic Vertex case without smoothing of estimat...
expdeg
ntriangles
Parameter estimation for static vertex case.
Parameter estimation for Vertex dynamics
Parameter estimation for Vertex model only for a list of dynamic netwo...
Parameter estimation for Vertex model only for a list of dynamic netwo...
General purpose regression engine for the methods bayesglm, glm and gl...
vdegree
Functions are provided to fit temporal lag models to dynamic networks. The models are build on top of exponential random graph models (ERGM) framework. There are functions for simulating or forecasting networks for future time points. Abhirup Mallik & Zack W. Almquist (2019) Stable Multiple Time Step Simulation/Prediction From Lagged Dynamic Network Regression Models, Journal of Computational and Graphical Statistics, 28:4, 967-979, <DOI: 10.1080/10618600.2019.1594834>.