Package: ergmito 0.3-1
ergmito: Exponential Random Graph Models for Small Networks
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.
Authors:
ergmito_0.3-1.tar.gz
ergmito_0.3-1.tar.gz(r-4.5-noble)ergmito_0.3-1.tar.gz(r-4.4-noble)
ergmito.pdf |ergmito.html✨
ergmito/json (API)
NEWS
# Install 'ergmito' in R: |
install.packages('ergmito', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/muriteams/ergmito/issues8 issues
Pkgdown site:https://muriteams.github.io
- fivenets - Example of a group of small networks
Last updated 2 years agofrom:0ec953ff37. Checks:2 OK, 1 NOTE. Indexed: no.
Target | Result | Latest binary |
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Doc / Vignettes | OK | Mar 27 2025 |
R-4.5-linux-x86_64 | NOTE | Mar 27 2025 |
R-4.4-linux-x86_64 | OK | Mar 27 2025 |
Exports:as_adjmatAVAILABLE_STATSbenchmarkitoblockdiagonalizecount_statsergm_blockdiagergmitoergmito_bootergmito_formulaeexact_gradientexact_hessianexact_loglikextract.ergmitogeodesicgeodesitagof_ergmitoinduced_submatis_directedmatrix_to_networknedgesnew_rergmitonnetsnvertexpowersetrbernoullisame_distsplitnetwork
Dependencies:askpasscachemclicodacurlDEoptimRergmevaluatefansifastmapgluehighrhttrjsonliteknitrlatticelifecyclelpSolveAPImagrittrMASSMatrixmemoisemimenetworkopensslpillarpkgconfigpurrrR6rbibutilsRcppRcppArmadilloRdpackrlangrlerobustbasestatnet.commonstringistringrsystexregtibbletrustutf8vctrsxfunyaml
Citation
When using ergmito, always cite this paper
Vega Yon G, Slaughter A, de la Haye K (2020). “Exponential Random Graph models for Little Networks.” Social Networks. doi:10.1016/j.socnet.2020.07.005, in press.
Use this if you are using the GitHub version of ergmito:
Vega Yon G (2023). ergmito: Exponential Random Graph Models for Small Networks. R package version 0.3-1 (wip), https://github.com/muriteams/ergmito.
Use this if you are using the CRAN version of ergmito:
Vega Yon G (2023). ergmito: Exponential Random Graph Models for Small Networks. R package version 0.3-1, https://cran.r-project.org/package=ergmito.
Corresponding BibTeX entries:
@Article{, title = {{Exponential Random Graph models for Little Networks}}, author = {George {Vega Yon} and Andrew Slaughter and Kayla {de la Haye}}, year = {{2020}}, note = {in press}, journal = {{Social Networks}}, doi = {10.1016/j.socnet.2020.07.005}, published = {Elsevier}, }
@Manual{, title = {{{ergmito: Exponential Random Graph Models for Small Networks}}}, author = {George {Vega Yon}}, year = {2023}, note = {R package version 0.3-1 (wip)}, url = {https://github.com/muriteams/ergmito}, }
@Manual{, title = {{{ergmito: Exponential Random Graph Models for Small Networks}}}, author = {George {Vega Yon}}, year = {2023}, note = {R package version 0.3-1}, publisher = {{CRAN}}, url = {https://cran.r-project.org/package=ergmito}, }