R: how to make passing of arguments using ... to multiple functions well-defined?

Question

V1: Suppose functions f(x, ...) and g(x , ...) can be passed different arguments. If I were to define a new function using both of them, can I make the passing of arguments via the ... operator well-defined? As a simple example:

f1 = function(x, n = 1) x + n
g1 = function(x, m = 1) x + m
f  = function(x, ...) f1(x, ...)
g  = function(x, ...) g1(x, ...)

h = function(x, ...) {

  fgList = list()
  fgList[["f"]] = f(x, ...)
  fgList[["g"]] = g(x, ...)
  return(fgList)
}

h(1:4)
#  $f
#  [1] 2 3 4 5

#  $g
#  [1] 2 3 4 5

h(1:4, n = 2)
#  Error in g1(x, ...) : unused argument (n = 2)

The argument n is being passed down to functions f and g, but it is only well-defined for function f. I want to mitigate against this.

V2: If they are functions that I have defined, then Hong Ooi's solution below works perfectly.

Can this solution be extended for pre-defined functions which don't have a ... argument or equivalently, can a ... argument be 'added' to a predefined function which doesn't have one? For example:

h = function(x, ...) mean(x, ...) * median (x, ...)
h(1:4, test = 1)
##  Error in median(x, ...) : unused argument (test = 1)

Answer 1

You can't have multiple versions of ... in the one environment. What you can do, however, is give each of your called sub-functions a ... argument of their own. This means they will ignore any parameters passed down that don't match their own formal arguments.

f1 = function(x, n = 1, ...) x + n
g1 = function(x, m = 1, ...) x + m

> h(1:4, n = 2)
$f
[1] 3 4 5 6

$g
[1] 2 3 4 5

Edit to answer added question: you can make a new version of median, which will override the predefined function when you call it in your own code. (Due to how R namespaces work, other predefined functions will still use the existing version.)

median <- function(x, na.rm=FALSE, ...)
base::median(x, na.rm)  # function median exported from base package