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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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  "Encoding": "UTF-8",
  "License": "MIT + file LICENSE",
  "VignetteBuilder": "knitr",
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  "URL": "https://muriteams.github.io/ergmito/",
  "BugReports": "https://github.com/muriteams/ergmito/issues",
  "Language": "en-US",
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  "Config/pak/sysreqs": "texlive libicu-dev libssl-dev",
  "Repository": "https://muriteams.r-universe.dev",
  "Date/Publication": "2025-12-20 00:09:29 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)",
  "Maintainer": "George Vega Yon <g.vegayon@gmail.com>",
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    "author": "Copilot <198982749+Copilot@users.noreply.github.com>",
    "committer": "GitHub <noreply@github.com>",
    "message": "Fix CRAN check: add missing package anchors in nvertex.Rd documentation (#27)\n\n* Initial plan\n\n* Fix CRAN check: add package anchors for external class references\n\nCo-authored-by: gvegayon <893619+gvegayon@users.noreply.github.com>\n\n* Adding devcontainer, new check, and fixing PR\n\n* Fixing README\n\n* Updating the README\n\n---------\n\nCo-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>\nCo-authored-by: gvegayon <893619+gvegayon@users.noreply.github.com>\nCo-authored-by: George G. Vega Yon <g.vegayon@gmail.com>",
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    "gof_ergmito",
    "induced_submat",
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    "matrix_to_network",
    "nedges",
    "new_rergmito",
    "nnets",
    "nvertex",
    "powerset",
    "rbernoulli",
    "same_dist",
    "splitnetwork"
  ],
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      "title": "Example of a group of small networks",
      "object": "fivenets",
      "class": [
        "list"
      ],
      "fields": [],
      "table": false,
      "tojson": false
    }
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      "title": "An alternative to 'as.matrix' to retrieve adjacency matrix fast",
      "topics": [
        "as_adjmat"
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    {
      "page": "benchmarkito",
      "title": "Utility to benchmark expression in R",
      "topics": [
        "benchmarkito"
      ]
    },
    {
      "page": "blockdiagonalize",
      "title": "Block-diagonal models using 'ergm'",
      "topics": [
        "blockdiagonalize",
        "ergm_blockdiag",
        "splitnetwork"
      ]
    },
    {
      "page": "check_convergence",
      "title": "Check the convergence of ergmito estimates",
      "topics": [
        "check_convergence",
        "check_support"
      ]
    },
    {
      "page": "count_stats",
      "title": "Count Network Statistics",
      "topics": [
        "AVAILABLE_STATS",
        "count_stats",
        "count_stats.formula",
        "count_stats.list"
      ]
    },
    {
      "page": "ergmito_boot",
      "title": "Bootstrap of ergmito",
      "topics": [
        "ergmito_boot"
      ]
    },
    {
      "page": "ergmito_formulae",
      "title": "Processing formulas in 'ergmito'",
      "topics": [
        "ergmito_formulae",
        "ergmito_loglik"
      ]
    },
    {
      "page": "ergmito_gof",
      "title": "Goodness of Fit diagnostics for ERGMito models",
      "topics": [
        "ergmito_gof",
        "gof_ergmito",
        "plot.ergmito_gof"
      ]
    },
    {
      "page": "exact_loglik",
      "title": "Vectorized calculation of ERGM exact log-likelihood",
      "topics": [
        "exact_gradient",
        "exact_gradient.default",
        "exact_hessian",
        "exact_loglik",
        "exact_loglik.default"
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    },
    {
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      "title": "Extract function to be used with the 'texreg' package.",
      "topics": [
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      ]
    },
    {
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      "title": "Example of a group of small networks",
      "topics": [
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      ]
    },
    {
      "page": "geodesic",
      "title": "Geodesic distance matrix (all pairs)",
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        "geodesic.matrix",
        "geodesic.network",
        "geodesita"
      ]
    },
    {
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      "title": "Extract a submatrix from a network",
      "topics": [
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      ]
    },
    {
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      "title": "Manipulation of network objects",
      "topics": [
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        "matrix_to_network.matrix"
      ]
    },
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      "page": "new_ergmito_ptr",
      "title": "Creates a new 'ergmito_ptr'",
      "topics": [
        "new_ergmito_ptr"
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      "title": "ERGMito sampler",
      "topics": [
        "new_rergmito",
        "[.ergmito_sampler"
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    },
    {
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      "title": "Utility functions to query network dimensions",
      "topics": [
        "is_directed",
        "nedges",
        "nnets",
        "nvertex"
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    },
    {
      "page": "plot.ergmito",
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      "topics": [
        "plot.ergmito"
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    {
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    {
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        "simulate.ergmito"
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