Ridge Regression Parameter Estimation.
ridgregextra: An R package for ridge regression parameter estimation
ridgregextra
focuses on finding the ridge parameter value k which makes the VIF values closest to 1 while keeping them above 1 as stressed "Applied Linear Statistical Models" (Kutner et al., 2004). The package includes the ridgereg_k
function, presents a system that automatically determines the k value in a certain range defined by the user and provides detailed ridge regression results. ridgereg_k
also provides ridge regression tables (VIF, MSE, R2, Beta, Stdbeta) using vif_k
function for k ridge parameter values generated between certain lower and upper bound values.
In addition, the ridge_reg
function provides users the ridge regression results for a manually entered k value. Finally ridgregextra
provides three sets of graphs consisting k versus VIF values, regression coefficents and standard errors of them.
ridgregextra
was presented for the first time in "Why R? Turkey 2022" conference.
Installing ridgregextra
from CRAN
install.packages("ridgregextra")
Installing ridgregextra
development version
Please make sure that you installed devtools
package.
If you would like to install dev version of the package, please use following command.
devtools::install_github(filizkrdg/ridgregextra)
Example usage of the package.
You can use isdals
package to have example data to test ridgregextra
package. isdals
package is being installed, while you are installing ridgregextra
package, so you don't have to install the package again.
- Prepare the dataset
library(isdals)
data(bodyfat)
x=bodyfat[,-1]
y=bodyfat[,1]
- Run
ridgereg_k
function to get coefficients by using alternative approach to traditional ridge regression techniques.
ridgereg_k(x,y,0,1)
You can use mctest
package to have example data to test ridgregextra
package. mctest
package is being installed, while you are installing ridgregextra
package, so you don't have to install the package again.
- Prepare the dataset
library("mctest")
x=Hald[,-1]
y=Hald[,1]
- Run
ridgereg_k
function to get coefficients by using alternative approach to traditional ridge regression techniques.
ridgereg_k(x,y,0,1)
References
- Kutner, M.H., Nachtsheim, C.J., Neter, J., Li, W., Applied Linear Statistical Models, pp.430-440, 2004.
- Karadağ, F. and Sazak, H.S., “R Algorithm for Ridge Parameter Estimation in Ridge Regression” Why R? Turkey 2022 Conference, online, Verbal, Summary Text, p.13, 2022. (https://www.nobelyayin.com/why-r-turkiye-2022-konferansi-18447.html)
Contact
For any questions please contact:
- Filiz Karadag, [email protected]
- Hakan Savas Sazak, [email protected]
- Olgun Aydin, [email protected].