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rdacca.hp  

Hierarchical and Variation Partitioning for Canonical Analysis
View on CRAN: Click here


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

Install from Github:
library("remotes")
install_github("cran/rdacca.hp")

Install by package version:
library("remotes")
install_version("rdacca.hp", "1.1-1")



Attach the package and use:
library("rdacca.hp")
Maintained by
Jiangshan Lai
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-12-04
Latest Update: 2023-05-23
Description:
This function conducts variation partitioning and hierarchical partitioning to calculate the unique, shared (referred as to "common") and individual contributions of each predictor (or matrix) towards explained variation (R-square and adjusted R-square) on canonical analysis (RDA,CCA and db-RDA), 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 .
How to cite:
Jiangshan Lai (2020). rdacca.hp: Hierarchical and Variation Partitioning for Canonical Analysis. R package version 1.1-1, https://cran.r-project.org/web/packages/rdacca.hp. Accessed 06 Nov. 2024.
Previous versions and publish date:
0.1.0 (2020-12-04 10:20), 0.2.0 (2021-01-18 07:00), 0.3.0 (2021-01-25 06:50), 0.5-3 (2021-02-06 09:50), 0.5-4 (2021-02-07 23:50), 0.5-5 (2021-02-27 06:40), 0.5-6 (2021-03-07 09:00), 1.0-1 (2021-08-11 09:50), 1.0-2 (2021-09-03 10:50), 1.0-3 (2021-09-14 09:50), 1.0-4 (2021-12-06 11:37), 1.0-5 (2022-01-12 13:42), 1.0-6 (2022-01-20 12:32), 1.0-7 (2022-01-30 15:00), 1.0-8 (2022-04-05 16:20), 1.0-9 (2023-02-09 16:10), 1.1-0 (2023-05-23 11:10)
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Complete documentation for rdacca.hp
Functions, R codes and Examples using the rdacca.hp R package
Some associated functions: creatbin . genList . odd . permu.hp . plot.rdaccahp . rdacca.hp . 
Some associated R codes: Full rdacca.hp package functions and examples
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