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) <arXiv:1804.04583> for a detailed description of the methods.

Version: 1.3
Depends: R (≥ 4.0.0), methods, Rcpp (≥ 0.9.4)
Imports: network, parallel, ggplot2, reshape2, intergraph, Matrix
LinkingTo: Rcpp, BH
Suggests: testthat, inline, knitr, rmarkdown, ergm, BH, igraph
Published: 2021-07-01
Author: Ian E. Fellows [aut, cre], Mark S. Handcock [ctb]
Maintainer: Ian E. Fellows <ian at>
License: MIT + file LICENCE
NeedsCompilation: yes
CRAN checks: lolog results


Reference manual: lolog.pdf
Vignettes: An Example Analysis Using lolog
An Introduction to LOLOG Network Models


Package source: lolog_1.3.tar.gz
Windows binaries: r-devel:, r-devel-UCRT:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): lolog_1.3.tgz, r-release (x86_64): lolog_1.3.tgz, r-oldrel: lolog_1.3.tgz
Old sources: lolog archive


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