best_lambda: Optimize the ridge parameter lambda with k-fold...

In emmmmmxj/bis557: Ridge Regression

Description

Optimize the ridge parameter lambda with k-fold cross-validation

Usage

best_lambda(formula, data, nfold = 5, lambda_list, intercept = TRUE)

Arguments

formula	An object of class formula to describe how the model is fitted
data	A data frame
nfold	An optional number k for k-fold cross-validation, default = 5
lambda_list	A numeric vector consisting of lambda candidates
intercept	An optional logical value to indicate if intercept is included, default = TRUE

Value

Return the best lambda value

Examples

data(iris)
best_lambda(formula = Sepal.Length ~ .,
            data = iris, nfold = 5,
            lambda_list = 10^seq(-2, 2, by = .1))

data(mtcars)
best_lambda(formula = mpg ~ drat + wt + qsec,
            data = mtcars, nfold = 3,
            lambda_list = 10^seq(-2, 2, by = .1))

emmmmmxj/bis557 documentation built on Nov. 4, 2019, 11:54 a.m.