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.
- Version1.3.1
- R versionunknown
- LicenseMIT
- LicenseLICENCE
- Needs compilation?Yes
- Last release12/07/2023
Documentation
Team
Ian E. Fellows
Mark S. Handcock
Show author detailsRolesContributor
Insights
Last 30 days
This package has been downloaded 540 times in the last 30 days. This could be a paper that people cite without reading. Reaching the medium popularity echelon is no small feat! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 5 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 9,426 times in the last 365 days. Impressive! The kind of number that makes colleagues ask, 'How did you do it?' The day with the most downloads was Sep 11, 2024 with 88 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Depends1 package
- Imports5 packages
- Suggests7 packages
- Linking To2 packages