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 |
| 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 |
| CRAN checks: |
ERPM results |
Documentation:
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