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UpSetVP  

An Alternative Visualization of VPA and HP in Canonical Analysis
View on CRAN: Click here


Download and install UpSetVP package within the R console
Install from CRAN:
install.packages("UpSetVP")

Install from Github:
library("remotes")
install_github("cran/UpSetVP")

Install by package version:
library("remotes")
install_version("UpSetVP", "1.0.0")



Attach the package and use:
library("UpSetVP")
Maintained by
Yao Liu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-05-03
Latest Update: 2022-05-03
Description:
Using matrix layout to visualize the unique, common, or individual contribution of each predictor (or matrix of predictors) towards explained variation on canonical analysis. These contributions were derived from variance partitioning analysis (VPA) and hierarchical partitioning (HP), applying the algorithm of Lai J., Zou Y., Zhang J., Peres-Neto P. (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>.
How to cite:
Yao Liu (2022). UpSetVP: An Alternative Visualization of VPA and HP in Canonical Analysis. R package version 1.0.0, https://cran.r-project.org/web/packages/UpSetVP. Accessed 21 Nov. 2024.
Previous versions and publish date:
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Complete documentation for UpSetVP
Functions, R codes and Examples using the UpSetVP R package
Some associated functions: UpSetVP-package . baima . barplot_hp . upset_vp . 
Some associated R codes: UpSetVP-package.R . baima.R . barplot_hp.R . upset_vp.R .  Full UpSetVP package functions and examples
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