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>.

Last updated 3 months ago

5.40 score 7 stars 11 scripts 1.1k downloads

rdacca.hp - Hierarchical Partitioning for Canonical Analysis

This function calculates the independent contribution of each explanatory variable to explained variation (R-squared) on RDA,CCA and db-RDA, applying the hierarchy algorithm of Chevan, A. and Sutherland, M. 1991 Hierarchical Partitioning.The American Statistician, 90-96 <DOI:10.1080/00031305.1991.10475776>.

Last updated 19 days ago

5.22 score 19 stars 1 dependents 29 scripts 794 downloads

gam.hp - Hierarchical Partitioning of Adjusted R2 and Explained Deviance for Generalized Additive Models

Conducts hierarchical partitioning to calculate individual contributions of each predictor towards adjusted R2 and explained deviance for generalized additive models based on output of gam()in 'mgcv' package, applying the algorithm in this paper: Lai(2024) <doi:10.1016/j.pld.2024.06.002>.

Last updated 3 months ago

4.95 score 6 stars 6 scripts 350 downloads

phylolm.hp - Hierarchical Partitioning of R2 for Phylogenetic Linear Regression

Conducts hierarchical partitioning to calculate individual contributions of phylogenetic tree and predictors (groups) towards total R2 for phylogenetic linear regression models.

Last updated 3 months ago

4.18 score 1 stars 225 downloads