CRAN/E | btergm

btergm

Temporal Exponential Random Graph Models by Bootstrapped Pseudolikelihood

Installation

About

Temporal Exponential Random Graph Models (TERGM) estimated by maximum pseudolikelihood with bootstrapped confidence intervals or Markov Chain Monte Carlo maximum likelihood. Goodness of fit assessment for ERGMs, TERGMs, and SAOMs. Micro-level interpretation of ERGMs and TERGMs. The methods are described in Leifeld, Cranmer and Desmarais (2018), JStatSoft doi:10.18637/jss.v083.i06.

Citation btergm citation info
github.com/leifeld/btergm

Key Metrics

Version 1.10.11
R ≥ 3.5
Published 2023-10-05 176 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks btergm results

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Maintainer

Maintainer

Philip Leifeld

philip.leifeld@essex.ac.uk

Authors

Philip Leifeld

aut / cre

Skyler J. Cranmer

ctb

Bruce A. Desmarais

ctb

Material

Reference manual
Package source

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

btergm archive

Depends

R ≥ 3.5

Imports

stats
utils
methods
graphics
network ≥ 1.17.1
sna ≥2.3.2
ergm ≥ 4.2.1
parallel
Matrix ≥ 1.3.2
boot ≥1.3.17
coda ≥ 0.18.1
ROCR ≥ 1.0.7
igraph ≥ 0.7.1
statnet.common ≥ 4.5.0

Suggests

fastglm ≥ 0.0.1
speedglm ≥ 0.3.1
testthat
Bergm ≥5.0.2
RSiena ≥ 1.0.12.232
ggplot2 ≥ 2.0.0

Reverse Imports

ergMargins
netmediate

Reverse Suggests

broom

Reverse Enhances

texreg