lolog: Latent Order Logistic Graph Models (original) (raw)
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 |
| DOI: | 10.32614/CRAN.package.lolog |
| Author: | Ian E. Fellows [aut, cre], Mark S. Handcock [ctb] |
| Maintainer: | Ian E. Fellows |
| License: | MIT + file |
| URL: | https://github.com/statnet/lolog |
| NeedsCompilation: | yes |
| CRAN checks: | lolog results |
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