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Simulate Dynamic Networks using Exponential Random Graph Models (ERGM) Family

v0.3.6 · Mar 9, 2026 · GPL-3
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Description

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>.

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14 OK
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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 17, 2026
NOTE 5 OK · 9 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026
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Dependency Network

Dependencies Reverse dependencies network ergm sna igraph arm glmnet dnr

Version History

new 0.3.6 Mar 10, 2026
updated 0.3.6 ← 0.3.5 diff Mar 9, 2026
updated 0.3.5 ← 0.3.4 diff Nov 29, 2020
updated 0.3.4 ← 0.3.2 diff Jul 25, 2018
new 0.3.2 Feb 22, 2018