glmm.hp
Hierarchical Partitioning of Marginal R2 for Generalized Mixed-Effect Models
Conducts hierarchical partitioning to calculate individual contributions of each predictor (fixed effects) towards marginal R2 for generalized linear mixed-effect model (including lm, glm and glmm) based on output of r.squaredGLMM() in 'MuMIn', applying the algorithm of Lai J.,Zou Y., Zhang S.,Zhang X.,Mao L.(2022)glmm.hp: an R package for computing individual effect of predictors in generalized linear mixed models.Journal of Plant Ecology,15(6)1302-1307
- Version0.1-6
- R version≥ 3.4.0
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- glmm.hp citation info
- Last release10/26/2024
Team
Jiangshan Lai
Kim Nimon
Show author detailsRolesAuthor
Insights
Last 30 days
Last 365 days
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
- Imports1 package