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  "Version": "0.3-2",
  "Title": "Exponential Random Graph Models for Small Networks",
  "Description": "Simulation and estimation of Exponential Random Graph\nModels (ERGMs) for small networks using exact statistics as\nshown in Vega Yon et al. (2020)\n<DOI:10.1016/j.socnet.2020.07.005>. As a difference from the\n'ergm' package, 'ergmito' circumvents using Markov-Chain\nMaximum Likelihood Estimator (MC-MLE) and instead uses Maximum\nLikelihood Estimator (MLE) to fit ERGMs for small networks. As\nexhaustive enumeration is computationally feasible for small\nnetworks, this R package takes advantage of this and provides\ntools for calculating likelihood functions, and other relevant\nfunctions, directly, meaning that in many cases both estimation\nand simulation of ERGMs for small networks can be faster and\nmore accurate than simulation-based algorithms.",
  "Authors@R": "c(\nperson(given = \"George\", family = \"Vega Yon\", role = c(\"cre\",\"aut\"),\nemail = \"g.vegayon@gmail.com\", comment = c(ORCID = \"0000-0002-3171-0844\")),\nperson(given = \"Kayla\", family = \"de la Haye\", role = c(\"ths\"),\ncomment = c(ORCID = \"0000-0002-2536-7701\")),\nperson(\"Army Research Laboratory and the U.S. Army Research Office\",\nrole = \"fnd\", comment = \"Grant Number W911NF-15-1-0577\")\n)",
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  "License": "MIT + file LICENSE",
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  "URL": "https://muriteams.github.io/ergmito/",
  "BugReports": "https://github.com/muriteams/ergmito/issues",
  "Language": "en-US",
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  "Repository": "https://muriteams.r-universe.dev",
  "Date/Publication": "2026-09-11 05:41:28 UTC",
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  "Author": "George Vega Yon [cre, aut] (ORCID:\n<https://orcid.org/0000-0002-3171-0844>),\nKayla de la Haye [ths] (ORCID: <https://orcid.org/0000-0002-2536-7701>),\nArmy Research Laboratory and the U.S. Army Research Office [fnd] (Grant\nNumber W911NF-15-1-0577)",
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      "page": "blockdiagonalize",
      "title": "Block-diagonal models using 'ergm'",
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        "ergm_blockdiag",
        "splitnetwork"
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    },
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      "title": "Check the convergence of ergmito estimates",
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        "check_support"
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        "count_stats",
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        "count_stats.list"
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        "ergmito_loglik"
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        "plot.ergmito_gof"
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