k_choose1: Selecting the optimal ridge regression parameters by GCV

In SC19037/SC19037: What the Package Does in One 'Title Case' Line

Description

Selecting the optimal ridge regression parameters by GCV

Usage

k_choose1(X, Y, kmax, N)

Arguments

X	the independent variable
Y	the response variable
kmax	the maximum value of the ridge regression parameter
N	the number of cross validation

Value

the optimal ridge regression parameter

Examples

## Not run: 
library(MASS)
data <- read.table("E:/Rcpp/data.txt", header = TRUE)
x <- as.matrix(data[,2:21])
y <- data[,1]
k_best1 <- k_choose1(x, y, kmax = 2, N = 2000)
print(k_best1)
 #compare with the optimal parameter gotten by existing ridge package 
select(lm.ridge(y~x, data = data, lambda = seq(0,2,0.001)))
## End(Not run)

SC19037/SC19037 documentation built on Jan. 3, 2020, 1:08 p.m.