ERPM: Exponential Random Partition Models
Simulates and estimates the Exponential Random Partition Model presented in the paper Hoffman, Block, and Snijders (2023) <doi:10.1177/00811750221145166>. It can also be used to estimate longitudinal partitions, following the model proposed in Hoffman and Chabot (2023) <doi:10.1016/j.socnet.2023.04.002>. The model is an exponential family distribution on the space of partitions (sets of non-overlapping groups) and is called in reference to the Exponential Random Graph Models (ERGM) for networks.
| Version: | 0.2.0 |
| Depends: | R (≥ 4.2) |
| Imports: | numbers, utils, stats,igraph,RColorBrewer,snowfall |
| Suggests: | knitr,rmarkdown,testthat (≥ 3.0.0) |
| Published: | 2024-05-10 |
| DOI: | 10.32614/CRAN.package.ERPM |
| Author: | Marion Hoffman [cre, aut, cph], Alexandra Amani [aut], Nico Keiser [aut] |
| Maintainer: | Marion Hoffman <marion.hoffman.31 at gmail.com> |
| BugReports: | https://github.com/stocnet/ERPM/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/stocnet/ERPM |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| In views: | NetworkAnalysis |
| CRAN checks: | ERPM results |
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