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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