Package: glmm.hp 0.1-6

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:Jiangshan Lai [aut, cre], Kim Nimon [aut]

glmm.hp_0.1-6.tar.gz
glmm.hp_0.1-6.tar.gz(r-4.5-noble)glmm.hp_0.1-6.tar.gz(r-4.4-noble)
glmm.hp_0.1-6.tgz(r-4.4-emscripten)glmm.hp_0.1-6.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://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/laijiangshan/glmm.hp/issues

2.78 score 5 scripts 901 downloads 32 mentions 5 exports 39 dependencies

Last updated 4 days agofrom:3caff806ef. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 27 2024
R-4.5-linuxOKOct 27 2024

Exports:creatbingenListglmm.hpoddplot.glmmhp

Dependencies:bootcliclustercolorspacefansifarverggplot2gluegtableinsightisobandlabelinglatticelifecyclelme4magrittrMASSMatrixmgcvminqaMuMInmunsellnlmenloptrpermutepillarpkgconfigR6RColorBrewerRcppRcppEigenrlangscalestibbleutf8vctrsveganviridisLitewithr