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: | 0.5-5 |
| Depends: | R (≥ 3.4.0), vegan, ggplot2 |
| Published: | 2021-02-27 |
| 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_0.5-5.tar.gz |
| Windows binaries: | r-devel: rdacca.hp_0.5-5.zip, r-release: rdacca.hp_0.5-4.zip, r-oldrel: rdacca.hp_0.5-4.zip |
| macOS binaries: | r-release: rdacca.hp_0.5-5.tgz, r-oldrel: rdacca.hp_0.5-4.tgz |
| Old sources: | rdacca.hp archive |
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