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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: | 1.3.1 |
| 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: | 2023-12-07 |
| 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 |
| CRAN checks: | lolog results |
| Reference manual: | lolog.pdf |
| Vignettes: |
An Example Analysis Using lolog An Introduction to LOLOG Network Models |
| Package source: | lolog_1.3.1.tar.gz |
| Windows binaries: | r-devel: lolog_1.3.1.zip, r-release: lolog_1.3.1.zip, r-oldrel: lolog_1.3.1.zip |
| macOS binaries: | r-release (arm64): lolog_1.3.1.tgz, r-oldrel (arm64): lolog_1.3.1.tgz, r-release (x86_64): lolog_1.3.1.tgz, r-oldrel (x86_64): lolog_1.3.1.tgz |
| Old sources: | lolog archive |
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