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 = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/muriteams/ergmito/issues
Pkgdown:https://muriteams.github.io
- fivenets - Example of a group of small networks
Last updated 1 years agofrom:0ec953ff37. Checks:OK: 1 NOTE: 1. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 27 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 27 2024 |
Exports:as_adjmatAVAILABLE_STATSbenchmarkitoblockdiagonalizecount_statsergm_blockdiagergmitoergmito_bootergmito_formulaeexact_gradientexact_hessianexact_loglikextract.ergmitogeodesicgeodesitagof_ergmitoinduced_submatis_directedmatrix_to_networknedgesnew_rergmitonnetsnvertexpowersetrbernoullisame_distsplitnetwork
Dependencies:askpasscachemclicodacurlDEoptimRergmevaluatefansifastmapgluehighrhttrjsonliteknitrlatticelifecyclelpSolveAPImagrittrMASSMatrixmemoisemimenetworkopensslpillarpkgconfigpurrrR6rbibutilsRcppRcppArmadilloRdpackrlangrlerobustbasestatnet.commonstringistringrsystexregtibbletrustutf8vctrsxfunyaml