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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