Type:	Package
Title:	Ridge Regression Parameter Estimation
Version:	0.1.1
Description:	It is a package that provides alternative approach for finding optimum parameters of ridge regression. This package focuses on finding the ridge parameter value k which makes the variance inflation factors closest to 1, while keeping them above 1 as addressed by Michael Kutner, Christopher Nachtsheim, John Neter, William Li (2004, ISBN:978-0073108742). Moreover, the package offers end-to-end functionality to find optimum k value and presents the detailed ridge regression results. Finally it shows three sets of graphs consisting k versus variance inflation factors, regression coefficients and standard errors of them.
License:	GPL (≥ 3)
Encoding:	UTF-8
URL:	https://github.com/filizkrdg/ridgregextra
BugReports:	https://github.com/filizkrdg/ridgregextra/issues
Depends:	R (≥ 4.0.0), plotly (≥ 4.9.0), isdals (≥ 3.0.0), mctest (≥ 1.3.0), stats(≥ 4.0.0), graphics(≥ 4.0.0)
RoxygenNote:	7.1.1
NeedsCompilation:	no
Packaged:	2023-11-25 21:39:09 UTC; olgunaydin
Author:	Filiz Karadag [aut], Hakan Savas Sazak [aut], Olgun Aydin [cre]
Maintainer:	Olgun Aydin <olgun.aydin@pg.edu.pl>
Repository:	CRAN
Date/Publication:	2023-11-25 21:50:02 UTC

Ridge regression results with a manually selected k value

Description

Ridge regression with a manually selected k value

Usage

ridge_reg(x, y, k)

Arguments

Value

A list of lists

Examples

library("mctest")
x <- Hald[,-1]
y <- Hald[,1]
k <- 0.1
ridge_reg(x,y,k)

library(isdals)
data(bodyfat)
x <- bodyfat[,-1]
y <- bodyfat[,1]
k <- 0.1
ridge_reg(x,y,k)

Ridge regression results with an automatically selected k value

Description

Ridge regression with a selected k value

Usage

ridgereg_k(x, y, a, b)

Arguments

Value

A list of lists

Examples

library("mctest")
x <- Hald[,-1]
y <- Hald[,1]
ridgereg_k(x,y,a=0,b=1)

library(isdals)
data(bodyfat)
x <- bodyfat[,-1]
y <- bodyfat[,1]
ridgereg_k(x,y,a=0,b=1)

Ridge regression tables in the range of given lower and upper bounds of k values

Description

Ridge regression tables in the range of given lower and upper bounds of k values

Usage

vif_k(x, y, a, b)

Arguments

Value

A list of lists

Examples

library("mctest")
x <- Hald[,-1]
y <- Hald[,1]
vif_k(x,y,a=0,b=1)

library(isdals)
data(bodyfat)
x <- bodyfat[,-1]
y <- bodyfat[,1]
vif_k(x,y,a=0,b=1)