glmm
Generalized Linear Mixed Models via Monte Carlo Likelihood Approximation
Approximates the likelihood of a generalized linear mixed model using Monte Carlo likelihood approximation. Then maximizes the likelihood approximation to return maximum likelihood estimates, observed Fisher information, and other model information.
- Version1.4.5
- R versionunknown
- LicenseGPL-2
- Needs compilation?Yes
- Last release09/22/2024
Documentation
Team
Christina Knudson
Charles J. Geyer
Show author detailsRolesContributorSydney Benson
Show author detailsRolesContributor
Insights
Last 30 days
This package has been downloaded 907 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 34 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 11,123 times in the last 365 days. The downloads are officially high enough to crash an underfunded departmental server. Quite an accomplishment! The day with the most downloads was Sep 26, 2024 with 106 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
- Depends4 packages
- Imports2 packages
- Suggests2 packages