Package: glmm.hp 0.1-5
Jiangshan Lai
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>.
Authors:
glmm.hp_0.1-5.tar.gz
glmm.hp_0.1-5.zip(r-4.5)glmm.hp_0.1-5.zip(r-4.4)glmm.hp_0.1-5.zip(r-4.3)
glmm.hp_0.1-5.tgz(r-4.4-any)glmm.hp_0.1-5.tgz(r-4.3-any)
glmm.hp_0.1-5.tar.gz(r-4.5-noble)glmm.hp_0.1-5.tar.gz(r-4.4-noble)
glmm.hp_0.1-5.tgz(r-4.4-emscripten)glmm.hp_0.1-5.tgz(r-4.3-emscripten)
glmm.hp.pdf |glmm.hp.html✨
glmm.hp/json (API)
# Install 'glmm.hp' in R: |
install.packages('glmm.hp', repos = c('https://laijiangshan.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/laijiangshan/glmm.hp/issues
Last updated 2 months agofrom:88a7180392. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 16 2024 |
R-4.5-win | OK | Oct 16 2024 |
R-4.5-linux | OK | Oct 16 2024 |
R-4.4-win | OK | Oct 16 2024 |
R-4.4-mac | OK | Oct 16 2024 |
R-4.3-win | OK | Oct 16 2024 |
R-4.3-mac | OK | Oct 16 2024 |
Exports:creatbingenListglmm.hpoddplot.glmmhp
Dependencies:bootcliclustercolorspacefansifarverggplot2gluegtableinsightisobandlabelinglatticelifecyclelme4magrittrMASSMatrixmgcvminqaMuMInmunsellnlmenloptrpermutepillarpkgconfigR6RColorBrewerRcppRcppEigenrlangscalestibbleutf8vctrsveganviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Hierarchical Partitioning of Marginal R2 for Generalized Mixed-Effect Models | glmm.hp |
Plot for a 'glmm.hp' object | plot.glmmhp |