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<doi:10.1093/jpe/rtac096>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0-0 |
rolling source/ R- | glmm.hp_1.0-0.tar.gz |
11.9 KiB |
1.0-0 |
rolling linux/jammy R-4.5 | glmm.hp_1.0-0.tar.gz |
56.8 KiB |
1.0-0 |
rolling linux/noble R-4.5 | glmm.hp_1.0-0.tar.gz |
56.7 KiB |
1.0-0 |
latest source/ R- | glmm.hp_1.0-0.tar.gz |
11.9 KiB |
1.0-0 |
latest linux/jammy R-4.5 | glmm.hp_1.0-0.tar.gz |
56.8 KiB |
1.0-0 |
latest linux/noble R-4.5 | glmm.hp_1.0-0.tar.gz |
56.7 KiB |
1.0-0 |
2026-04-23 source/ R- | glmm.hp_1.0-0.tar.gz |
11.9 KiB |
1.0-0 |
2026-04-09 windows/windows R-4.5 | glmm.hp_1.0-0.zip |
59.3 KiB |
0.1-8 |
2025-04-20 source/ R- | glmm.hp_0.1-8.tar.gz |
9.5 KiB |