CRAN/E | ergmito

ergmito

Exponential Random Graph Models for Small Networks

Installation

About

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.

Citation ergmito citation info
muriteams.github.io/ergmito/
Bug report File report

Key Metrics

Version 0.3-0
R ≥ 3.3.0
Published 2020-08-10 1355 days ago
Needs compilation? yes
License MIT
License File
CRAN checks ergmito results
Language en-US

Downloads

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Last 30 days 198 +2%
Last 90 days 578 -28%
Last 365 days 2.456 -31%

Maintainer

Maintainer

George Vega Yon

g.vegayon@gmail.com

Authors

George Vega Yon

cre / aut

Kayla de la Haye

ths

Army Research Laboratory
the U.S. Army Research Office

fnd

(Grant Number W911NF-15-1-0577)

Material

NEWS
Reference manual
Package source

Vignettes

ERGM equations
Extending ergmito

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

ergmito archive

Depends

R ≥ 3.3.0

Imports

ergm
network
MASS
Rcpp
texreg
stats
parallel
utils
methods
graphics

Suggests

covr
sna
lmtest
fmcmc
coda
knitr
rmarkdown
tinytest

LinkingTo

Rcpp
RcppArmadillo