dnr
Simulate Dynamic Networks using Exponential Random Graph Models (ERGM) Family
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.
- Version0.3.5
- R version≥ 3.2.0
- LicenseGPL-3
- Needs compilation?No
- Last release11/30/2020
Documentation
Team
Abhirup Mallik
Zack Almquist
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Last 30 days
This package has been downloaded 152 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,092 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 29 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Depends2 packages
- Imports4 packages
- Suggests2 packages