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: 1.1
Depends: R (≥ 3.0.0), methods, Rcpp (≥ 0.9.4)
Imports: network, parallel, ggplot2, reshape2, intergraph, Matrix
LinkingTo: Rcpp, BH
Suggests: testthat, inline, knitr, rmarkdown, ergm, BH, igraph
Published: 2018-10-22
Author: c(person(c("Ian","E."),"Fellows", role=c("aut","cre"), email="ian@fellstat.com"), person(c("Mark","S."),"Handcock", role="ctb"))
Maintainer: Ian E. Fellows <ian at fellstat.com>
License: MIT + file LICENCE
URL: https://github.com/statnet/lolog
NeedsCompilation: yes
Materials: README
CRAN checks: lolog results

Downloads:

Reference manual: lolog.pdf
Vignettes: An Example Analysis Using lolog
An Introduction to LOLOG Network Models
Package source: lolog_1.1.tar.gz
Windows binaries: r-devel: lolog_1.1.zip, r-release: lolog_1.1.zip, r-oldrel: lolog_1.1.zip
OS X binaries: r-release: lolog_1.1.tgz, r-oldrel: lolog_1.1.tgz
Old sources: lolog archive

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