Other packages > Find by keyword >

rwa  

Perform a Relative Weights Analysis
View on CRAN: Click here


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

Install from Github:
library("remotes")
install_github("cran/rwa")

Install by package version:
library("remotes")
install_version("rwa", "0.0.3")



Attach the package and use:
library("rwa")
Maintained by
Martin Chan
[Scholar Profile | Author Map]
First Published: 2020-11-24
Latest Update: 2020-11-24
Description:
Perform a Relative Weights Analysis (RWA) (a.k.a. Key Drivers Analysis) as per the method described in Tonidandel & LeBreton (2015) , with its original roots in Johnson (2000) . 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.
How to cite:
Martin Chan (2020). rwa: Perform a Relative Weights Analysis. R package version 0.0.3, https://cran.r-project.org/web/packages/rwa. Accessed 16 Apr. 2025.
Previous versions and publish date:
No previous versions
Other packages that cited rwa R package
View rwa citation profile
Other R packages that rwa depends, imports, suggests or enhances
Complete documentation for rwa
Functions, R codes and Examples using the rwa R package
Some associated functions: pipe . plot_rwa . remove_all_na_cols . rwa . 
Some associated R codes: globals.R . plot_rwa.R . remove_all_na_cols.R . rwa.R . utils-pipe.R .  Full rwa package functions and examples
Downloads during the last 30 days
03/1703/1803/1903/2003/2103/2203/2303/2403/2503/2603/2703/2803/2903/3003/3104/0104/0204/0304/0404/0504/0604/0704/0804/0904/1004/1104/1204/1304/14Downloads for rwa05101520253035TrendBars

Today's Hot Picks in Authors and Packages

hkclustering  
Ensemble Clustering using K Means and Hierarchical Clustering
Implements an ensemble algorithm for clustering combining a k-means and a hierarchical clustering ap ...
Download / Learn more Package Citations See dependency  
apache.sedona  
R Interface for Apache Sedona
R interface for 'Apache Sedona' based on 'sparklyr' (). ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
MM4LMM  
Inference of Linear Mixed Models Through MM Algorithm
The main function MMEst() performs (Restricted) Maximum Likelihood in a variance component mixed mod ...
Download / Learn more Package Citations See dependency  
datadictionary  
Create a Data Dictionary
Creates a data dictionary from any dataframe or tibble in your R environment. You can opt to add va ...
Download / Learn more Package Citations See dependency  
MultiKink  
Estimation and Inference for Multi-Kink Quantile Regression
Estimation and inference for multiple kink quantile regression for longitudinal data and the i.i.d d ...
Download / Learn more Package Citations See dependency  

24,012

R Packages

207,311

Dependencies

64,993

Author Associations

24,013

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA