lolog: Latent Order Logistic Graph Models

Estimation of Latent Order Logistic (LOLOG) Models for Networks. LOLOGs are a flexible and fully general class of statistical graph models. This package provides functions for performing MOM, GMM and variational inference. Visual diagnostics and goodness of fit metrics are provided. See Fellows (2018) <doi:10.48550/arXiv.1804.04583> for a detailed description of the methods.

Version:	1.3.2
Depends:	R (≥ 4.0.0), methods, Rcpp (≥ 0.9.4)
Imports:	network, parallel, ggplot2, reshape2, intergraph, Matrix
LinkingTo:	Rcpp, BH
Suggests:	testthat (≥ 3.0.0), inline, knitr, rmarkdown, ergm, BH, igraph
Published:	2025-09-03
DOI:	10.32614/CRAN.package.lolog
Author:	Ian E. Fellows [aut, cre], Mark S. Handcock [ctb]
Maintainer:	Ian E. Fellows <ian at fellstat.com>
License:	MIT + file LICENCE
URL:	https://github.com/statnet/lolog
NeedsCompilation:	yes
In views:	NetworkAnalysis
CRAN checks:	lolog results

Documentation:

Reference manual:	lolog.html , lolog.pdf
Vignettes:	An Example Analysis Using lolog (source, R code) An Introduction to LOLOG Network Models (source, R code)

Downloads:

Package source:	lolog_1.3.2.tar.gz
Windows binaries:	r-devel: lolog_1.3.2.zip, r-release: lolog_1.3.2.zip, r-oldrel: lolog_1.3.2.zip
macOS binaries:	r-release (arm64): lolog_1.3.2.tgz, r-oldrel (arm64): lolog_1.3.2.tgz, r-release (x86_64): lolog_1.3.2.tgz, r-oldrel (x86_64): lolog_1.3.2.tgz
Old sources:	lolog archive

Reverse dependencies:

Reverse imports:	MinTriadic
Reverse linking to:	MinTriadic

Linking:

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