<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Exponential Random Partition Models</dc:title>
  <dc:title>R package ERPM version 0.2.0</dc:title>
  <dc:subject>CRAN Task View: NetworkAnalysis (https://CRAN.R-project.org/view=NetworkAnalysis)</dc:subject>
  <dc:description>Simulates and estimates the Exponential Random Partition Model presented 
    in the paper Hoffman, Block, and Snijders (2023) &lt;doi:10.1177/00811750221145166&gt;. 
    It can also be used to estimate longitudinal partitions, following the model 
    proposed in Hoffman and Chabot (2023) &lt;doi:10.1016/j.socnet.2023.04.002&gt;. 
    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.</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 4.2)</dc:relation>
  <dc:relation>Imports: numbers, utils, stats, igraph, RColorBrewer, snowfall</dc:relation>
  <dc:relation>Suggests: knitr, rmarkdown, testthat (&gt;= 3.0.0)</dc:relation>
  <dc:creator>Marion Hoffman &lt;marion.hoffman.31@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Marion Hoffman [cre, aut, cph] (ORCID:
    &lt;https://orcid.org/0000-0002-0741-7760&gt;),
  Alexandra Amani [aut],
  Nico Keiser [aut]</dc:contributor>
  <dc:rights>GPL (&gt;= 3)</dc:rights>
  <dc:date>2024-05-10</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=ERPM</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.ERPM</dc:identifier>
</oai_dc:dc>
