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mdw  

Maximum Diversity Weighting
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("mdw", "2024.8-1")



Attach the package and use:
library("mdw")
Maintained by
Youyi Fong
[Scholar Profile | Author Map]
First Published: 2017-08-28
Latest Update: 2020-06-18
Description:
Dimension-reduction methods aim at defining a score that maximizes signal diversity. Three approaches, tree weight, maximum entropy weights, and maximum variance weights are provided. These methods are described in He and Fong (2019) .
How to cite:
Youyi Fong (2017). mdw: Maximum Diversity Weighting. R package version 2024.8-1, https://cran.r-project.org/web/packages/mdw. Accessed 31 Mar. 2025.
Previous versions and publish date:
2017.8-27 (2017-08-28 14:10), 2017.12-03 (2017-12-04 11:27), 2020.6-17 (2020-06-18 12:30)
Other packages that cited mdw R package
View mdw citation profile
Other R packages that mdw depends, imports, suggests or enhances
Complete documentation for mdw
Functions, R codes and Examples using the mdw R package
Some associated functions: asym.v.e . asym.v.v . entropy.weight . get.bw . mdw . pca.weight . tree.weight . var.weight . 
Some associated R codes: asym.v.e.R . asym.v.v.R . entropy.weight.R . get.bw.R . non-normal_categrical_data_generation.R . pca.weight.R . tree_weight.R . var.weight.R .  Full mdw package functions and examples
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