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()' and 'bam()' in 'mgcv' package, applying the algorithm in this paper: Lai(2024) <doi:10.1016/j.pld.2024.06.002>.
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5.46 score 9 stars 32 scripts 358 downloadsglmm.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>.
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4.96 score 9 stars 1 dependents 34 scripts 943 downloadsrdacca.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>.
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4.84 score 22 stars 46 scripts 1.4k downloadsphylolm.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.
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4.00 score 2 stars 1 scripts 217 downloads