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 |
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
x |
Explanatory variables (Dataframe, matrix) |
y |
Dependent variables (Dataframe, vector) |
k |
Ridge parameter |
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
x |
Explanatory variables (Dataframe, matrix) |
y |
Dependent variables (Dataframe, vector) |
a |
Lower bound of k |
b |
Upper bound of k |
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
x |
Explanatory variables (Dataframe, matrix) |
y |
Dependent variables (Dataframe, vector) |
a |
Lower bound of k |
b |
Upper bound of k |
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)