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ergmito  

Exponential Random Graph Models for Small Networks
View on CRAN: Click here


Download and install ergmito package within the R console
Install from CRAN:
install.packages("ergmito")

Install from Github:
library("remotes")
install_github("cran/ergmito")

Install by package version:
library("remotes")
install_version("ergmito", "0.3-2")



Attach the package and use:
library("ergmito")
Maintained by
George Vega Yon
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-02-01
Latest Update: 2025-09-03
Description:
Simulation and estimation of Exponential Random Graph Models (ERGMs) for small networks using exact statistics as shown in Vega Yon et al. (2020) . 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.
How to cite:
George Vega Yon (2020). ergmito: Exponential Random Graph Models for Small Networks. R package version 0.3-2, https://cran.r-project.org/web/packages/ergmito. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.2-0 (2020-02-01 11:40), 0.2-1 (2020-02-12 18:20), 0.3-0 (2020-08-10 23:40), 0.3-1 (2023-06-14 12:42)
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Complete documentation for ergmito
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