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  "Version": "1.11.1",
  "Date": "2025-03-19",
  "Title": "Temporal Exponential Random Graph Models by Bootstrapped\nPseudolikelihood",
  "Authors@R": "c(person(given = \"Philip\", family = \"Leifeld\", email = \"philip.leifeld@manchester.ac.uk\", role = c(\"aut\", \"cre\")), person(given = c(\"Skyler\", \"J.\"), family = \"Cranmer\", email = \"cranmer.12@osu.edu\", role = \"ctb\"), person(given = c(\"Bruce\", \"A.\"), family = \"Desmarais\", email = \"bdesmarais@psu.edu\", role = \"ctb\"))",
  "Description": "Temporal Exponential Random Graph Models (TERGM) estimated\nby maximum pseudolikelihood with bootstrapped confidence\nintervals or Markov Chain Monte Carlo maximum likelihood.\nGoodness of fit assessment for ERGMs, TERGMs, and SAOMs.\nMicro-level interpretation of ERGMs and TERGMs. The methods are\ndescribed in Leifeld, Cranmer and Desmarais (2018), JStatSoft\n<doi:10.18637/jss.v083.i06>.",
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  "Repository": "https://leifeld-lab.r-universe.dev",
  "Date/Publication": "2025-03-19 00:44:54 UTC",
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