rdacca.hp: Hierarchical and Variation Partitioning for Canonical Analysis

This function conducts variation partitioning and hierarchical partitioning to calculate the unique, shared (referred as to "common") and independent contributions of each predictor (or matrix) to explained variation (R-squared and adjusted R-squared) on canonical analysis (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>.

Version: 0.5-6
Depends: R (≥ 3.4.0), vegan, ggplot2
Published: 2021-03-07
Author: Jiangshan Lai,Pedro Peres-Neto
Maintainer: Jiangshan Lai <lai at ibcas.ac.cn>
License: GPL-2 | GPL-3 [expanded from: GPL]
URL: https://github.com/laijiangshan/rdacca.hp
NeedsCompilation: no
CRAN checks: rdacca.hp results


Reference manual: rdacca.hp.pdf
Package source: rdacca.hp_0.5-6.tar.gz
Windows binaries: r-devel: rdacca.hp_0.5-6.zip, r-release: rdacca.hp_0.5-6.zip, r-oldrel: rdacca.hp_0.5-6.zip
macOS binaries: r-release (arm64): rdacca.hp_0.5-6.tgz, r-release (x86_64): rdacca.hp_0.5-6.tgz, r-oldrel: rdacca.hp_0.5-6.tgz
Old sources: rdacca.hp archive


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