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: NA
Author: Marion Hoffman ORCID iD [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:

Reference manual: ERPM.pdf

Downloads:

Package source: ERPM_0.2.0.tar.gz
Windows binaries: r-devel: ERPM_0.2.0.zip, r-release: ERPM_0.2.0.zip, r-oldrel: ERPM_0.2.0.zip
macOS binaries: r-release (arm64): ERPM_0.2.0.tgz, r-oldrel (arm64): ERPM_0.2.0.tgz, r-release (x86_64): ERPM_0.2.0.tgz, r-oldrel (x86_64): ERPM_0.2.0.tgz

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