Remove dependent variable from formula for model.matrix

Question

I'm just learning how to deal with model.matrix . For example, to create out-of-sample predictions I extract the formula from my model, say it's a linear model. Using the function formula(mymodel) extracts that:

form <- formula(y ~ x1 + x2 * x3)

Now, to create predictions I need a model.matrix without my y . I could type that by hand:

X <- model.matrix(~ x1 + x2 * x3, data=out.of.sample.data)

However, is there a way using, for example, update to get rid of the left part my formula?

Thanks!

Answer 1

It can be done with update by setting the response variable to NULL :

form <- formula(y ~ x1 + x2 * x3)
newform <- update(form, NULL ~ .)

Answer 2

This is how I usually do this. I'm not aware of a built-in function for this.

df = data.frame(y=rnorm(10), x1=rnorm(10), x2=rnorm(10), x3=rnorm(10))
mymodel = lm(y ~ x1 + x2 + x3, df)
form_vars_only = 
  formula(paste("~",strsplit(as.character(formula(mymodel)),"~")[[3]]))