The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

rwa: Perform a Relative Weights Analysis

Perform a Relative Weights Analysis (RWA) (a.k.a. Key Drivers Analysis) as per the method described in Tonidandel & LeBreton (2015) <doi:10.1007/s10869-014-9351-z>, with its original roots in Johnson (2000) <doi:10.1207/S15327906MBR3501_1>. In essence, RWA decomposes the total variance predicted in a regression model into weights that accurately reflect the proportional contribution of the predictor variables, which addresses the issue of multi-collinearity. In typical scenarios, RWA returns similar results to Shapley regression, but with a significant advantage on computational performance.

Version: 0.0.3
Imports: dplyr, magrittr, stats, tidyr, ggplot2
Published: 2020-11-24
DOI: 10.32614/CRAN.package.rwa
Author: Martin Chan
Maintainer: Martin Chan <martinchan53 at gmail.com>
BugReports: https://github.com/martinctc/rwa/issues
License: GPL-3
URL: https://github.com/martinctc/rwa
NeedsCompilation: no
Materials: README NEWS
CRAN checks: rwa results

Documentation:

Reference manual: rwa.pdf

Downloads:

Package source: rwa_0.0.3.tar.gz
Windows binaries: r-devel: rwa_0.0.3.zip, r-release: rwa_0.0.3.zip, r-oldrel: rwa_0.0.3.zip
macOS binaries: r-release (arm64): rwa_0.0.3.tgz, r-oldrel (arm64): rwa_0.0.3.tgz, r-release (x86_64): rwa_0.0.3.tgz, r-oldrel (x86_64): rwa_0.0.3.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=rwa to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.