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. Stable Multiple Time Step Simulation/Prediction from Lagged Dynamic Network Regression Models. Mallik, Almquist (2017, under review).
| Version: | 0.3.4 |
| Depends: | R (≥ 3.2.0), network, ergm |
| Imports: | sna, igraph, arm, glmnet |
| Suggests: | testthat, knitr |
| Published: | 2018-07-26 |
| Author: | Abhirup Mallik [aut, cre], Zack Almquist [aut] |
| Maintainer: | Abhirup Mallik <malli066 at umn.edu> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | dnr results |
| Reference manual: | dnr.pdf |
| Vignettes: |
Dynamic Network Regression Using dnr |
| Package source: | dnr_0.3.4.tar.gz |
| Windows binaries: | r-devel: dnr_0.3.4.zip, r-release: dnr_0.3.4.zip, r-oldrel: dnr_0.3.4.zip |
| macOS binaries: | r-release: dnr_0.3.4.tgz, r-oldrel: dnr_0.3.4.tgz |
| Old sources: | dnr archive |
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