18. Explore 6.12 In-Depth Discovery Guide

{
# Add a column of 1s for the intercept
X = cbind(1, X)

# Calculate the linear predictor
mu = X %*% par

# Calculate the sum squared error
error = sum((y - mu)^2)

# Add the penalty term
value = error + lambda * sum(par^2)

return(value)

}