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upset.hp: Generate UpSet Plots of VP and HP Based on the ASV Concept

Using matrix layout to visualize the unique, common, or individual contribution of each predictor (or matrix of predictors) towards explained variation on different models. These contributions were derived from variation partitioning (VP) and hierarchical partitioning (HP), applying the algorithm of "Lai et al. (2022) Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package.Methods in Ecology and Evolution, 13: 782-788 <doi:10.1111/2041-210X.13800>".

Version: 0.0.1
Depends: R (≥ 3.6.0)
Imports: MuMIn, vegan, glmm.hp, ggplot2, patchwork, grDevices
Published: 2025-06-04
DOI: 10.32614/CRAN.package.upset.hp
Author: Jiangshan Lai ORCID iD [aut, cre], Yao Liu [aut]
Maintainer: Jiangshan Lai <lai at njfu.edu.cn>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/laijiangshan/upset.hp
NeedsCompilation: no
CRAN checks: upset.hp results

Documentation:

Reference manual: upset.hp.pdf

Downloads:

Package source: upset.hp_0.0.1.tar.gz
Windows binaries: r-devel: upset.hp_0.0.1.zip, r-release: upset.hp_0.0.1.zip, r-oldrel: upset.hp_0.0.1.zip
macOS binaries: r-release (arm64): upset.hp_0.0.1.tgz, r-oldrel (arm64): upset.hp_0.0.1.tgz, r-release (x86_64): upset.hp_0.0.1.tgz, r-oldrel (x86_64): upset.hp_0.0.1.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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