my_ridge_xval: Finding optimal lambda using out of sample cross validation
In kimgannon/bis557: Contains Homework Assignments for BIS 557 2020

This function cross-validates a ridge regression model for out of sample accuracy for several lambdas, then finds the optimal lambda. We choose lambda that yields the lowest mean squared difference in out-of-sample residuals

1	my_ridge_xval(f, d, lambdas, flds)

`f`	a formula the data will be fit to
`d`	the data to be fit (a data frame)
`lambdas`	a vector of candidate ridge parameters
`flds`	a list of folds

data("iris")
irisform <- Sepal.Length ~.
irisfold <- rsample::vfold_cv(iris)
lambda_vec <- seq(1,100,by=0.1)
my_ridge_xval(irisform, iris, lambda_vec, irisfold)