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GGRidge  

Graphical Group Ridge
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("GGRidge", "1.1.0")



Attach the package and use:
library("GGRidge")
Maintained by
Saeed Aldahmani
[Scholar Profile | Author Map]
First Published: 2021-03-02
Latest Update: 2021-03-02
Description:
The Graphical Group Ridge 'GGRidge' package package classifies ridge regression predictors in disjoint groups of conditionally correlated variables and derives different penalties (shrinkage parameters) for these groups of predictors. It combines the ridge regression method with the graphical model for high-dimensional data (i.e. the number of predictors exceeds the number of cases) or ill-conditioned data (e.g. in the presence of multicollinearity among predictors). The package reduces the mean square errors and the extent of over-shrinking of predictors as compared to the ridge method.Aldahmani, S. and Zoubeidi, T. (2020) .
How to cite:
Saeed Aldahmani (2021). GGRidge: Graphical Group Ridge. R package version 1.1.0, https://cran.r-project.org/web/packages/GGRidge. Accessed 09 May. 2025.
Previous versions and publish date:
0.1.0 (2021-03-02 11:10)
Other packages that cited GGRidge R package
View GGRidge citation profile
Other R packages that GGRidge depends, imports, suggests or enhances
Complete documentation for GGRidge
Functions, R codes and Examples using the GGRidge R package
Some associated functions: GGRidge-package . GGRidge . SampleEyeData . 
Some associated R codes: GGRidge.R .  Full GGRidge package functions and examples
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