Package: rdacca.hp
Type: Package
Title: Hierarchical and Variation Partitioning for Canonical Analysis
        Without Limits for the Number of Predictors (Matrices)
Version: 0.5-3
Date: 2021-2-6
Depends: R (>= 3.4.0),vegan,ggplot2
Author: Jiangshan Lai,Pedro Peres-neto
Maintainer: Jiangshan Lai <lai@ibcas.ac.cn>
Description: 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>. 
License: GPL
URL: https://github.com/laijiangshan/rdacca.hp
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-06 08:30:27 UTC; Thinkpad
Repository: CRAN
Date/Publication: 2021-02-06 08:50:03 UTC
