Let's take the following example:
set.seed(342) x1 <- runif(100) x2 <- runif(100) y <- x1+x2 + 2*x1*x2 + rnorm(100) fit <- lm(y~x1*x2)
This creates a model of y based on x1 and x2, using a OLS regression. If we wish to predict y for a given x_vec we could simply use the formula we get from the
However, what if we want to predict the lower and upper predictions of y? (for a given confidence level).
How then would we build the formula?