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: | 0.3.2 |
| Depends: | R (≥ 3.2.0), network, ergm |
| Imports: | sna, igraph, arm, glmnet |
| Suggests: | testthat, knitr |
| Published: | 2018-02-23 |
| 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: |
A Bootstrap Based Multiple Hypothesis Testing Procedure |
| Package source: | dnr_0.3.2.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| OS X El Capitan binaries: | r-release: dnr_0.3.2.tgz |
| OS X Mavericks binaries: | r-oldrel: not available |
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