Package: ergmito
Version: 0.3-2
Title: Exponential Random Graph Models for Small Networks
Description: Simulation and estimation of Exponential Random Graph
        Models (ERGMs) for small networks using exact statistics as
        shown in Vega Yon et al. (2020)
        <DOI:10.1016/j.socnet.2020.07.005>. As a difference from the
        'ergm' package, 'ergmito' circumvents using Markov-Chain
        Maximum Likelihood Estimator (MC-MLE) and instead uses Maximum
        Likelihood Estimator (MLE) to fit ERGMs for small networks. As
        exhaustive enumeration is computationally feasible for small
        networks, this R package takes advantage of this and provides
        tools for calculating likelihood functions, and other relevant
        functions, directly, meaning that in many cases both estimation
        and simulation of ERGMs for small networks can be faster and
        more accurate than simulation-based algorithms.
Depends: R (>= 3.3.0)
Authors@R: c(
      person(given = "George", family = "Vega Yon", role = c("cre","aut"),
      email = "g.vegayon@gmail.com", comment = c(ORCID = "0000-0002-3171-0844")),
      person(given = "Kayla", family = "de la Haye", role = c("ths"),
      comment = c(ORCID = "0000-0002-2536-7701")),
      person("Army Research Laboratory and the U.S. Army Research Office",
      role = "fnd", comment = "Grant Number W911NF-15-1-0577")
      )
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Encoding: UTF-8
Imports: ergm, network, MASS, Rcpp, texreg, stats, parallel, utils,
        methods, graphics
LinkingTo: Rcpp, RcppArmadillo
License: MIT + file LICENSE
Suggests: covr, sna, lmtest, fmcmc, coda, knitr, rmarkdown, tinytest
VignetteBuilder: knitr
LazyData: true
URL: https://muriteams.github.io/ergmito/
BugReports: https://github.com/muriteams/ergmito/issues
Language: en-US
NeedsCompilation: yes
Config/pak/sysreqs: texlive libicu-dev libssl-dev
Repository: https://muriteams.r-universe.dev
Date/Publication: 2025-12-20 00:09:29 UTC
RemoteUrl: https://github.com/muriteams/ergmito
RemoteRef: HEAD
RemoteSha: 134e2c866dc9e05a0069f9e83aadd6e1661c16c5
Packaged: 2026-06-18 08:31:31 UTC; root
Author: George Vega Yon [cre, aut] (ORCID:
    <https://orcid.org/0000-0002-3171-0844>),
  Kayla de la Haye [ths] (ORCID: <https://orcid.org/0000-0002-2536-7701>),
  Army Research Laboratory and the U.S. Army Research Office [fnd] (Grant
    Number W911NF-15-1-0577)
Maintainer: George Vega Yon <g.vegayon@gmail.com>