When to use missing versus NULL values for passing undefined function arguments in R, and why?

Question

To date when writing R functions I\'ve passed undefined arguments as NULL values and then tested whether they are NULL i.e.

f1 <- function (x = NULL) {
           


        

Answer 1

In my opinion, it is not clear when the limitation to missing applies. The documentation, as you quote, says that missing can only be used in the immediate body of the function. A simple example, though, shows that that is not the case and that it works as expected when the arguments are passed to a nested function.

f1 = function(x, y, z){
  if(!missing(x))
    print(x)
  if(!missing(y))
    print(y)
}

f2 = function(x, y, z){
  if(!missing(z)) print(z)
  f1(x, y)
}
f1(y="2")
#> [1] "2"
f2(y="2", z="3")
#> [1] "3"
#> [1] "2"
f2(x="1", z="3")
#> [1] "3"
#> [1] "1"

I would like to see an example of a case when missing does not work in a nested function.

^{Created on 2019-09-30 by the reprex package (v0.2.1)}