R: function parameters inheritance

Question

So i have the following code:

library(semPLS)
data(ECSImobi)

#exponent vector for transformation of the dataset
#model of type plsm
#data 
#returns a list of models with length of exponent vector
#list items are of class sempls
CalcModels <- function(exponent,model,data){

  #initialize result as list
  result <- vector("list")

  #estimate models with different distances
  for(i in seq_along(exponent)){
    result[[i]] <- sempls(model=model, data = data^exponent[i])
  }

  return(result)

}

#calculate ecsi models with exponent 0.1, 0.2, ..., 2.0
ecsiModels <- CalcModels(c(1:20/10),ECSImobi,mobi)

The sempls() function has numerous other parameters. Is there any way I can give them to the CalcModels function, so I can call the CalcModels function with the additional parameter wscheme="pw" of the sempls function. I could write them all in the parameters of both functions, but I think there must be a smarter way that I'm missing.

So I want something like that:

library(semPLS)
data(ECSImobi)

#exponent vector for transformation of the dataset
#model of type plsm
#data 
#returns a list of models with length of exponent vector
#list items are of class sempls
CalcModels <- function(exponent,model,data,wscheme){

  #initialize result as list
  result <- vector("list")

  #estimate models with different distances
  for(i in seq_along(exponent)){
    result[[i]] <- sempls(model=model, data = data^exponent[i],wscheme=wscheme)
  }

  return(result)

}

#calculate ecsi models with exponent 0.1, 0.2, ..., 2.0
ecsiModels <- CalcModels(c(1:20/10),ECSImobi,mobi,"pw")

but instead of writing each parameter in both functions do some kind of inheritance of the parameters without overwriting the function.

Answer 1

Would you like to use ellipsis (see here for more details)? This is a very useful technique to pass arguments to another function. All you would need to do is to add ... to the definition of function:

CalcModels <- function(exponent,model,data,...){

  #initialize result as list
  result <- vector("list")

  #estimate models with different distances
  for(i in seq_along(exponent)){
    result[[i]] <- sempls(model=model, data = data^exponent[i],...)
  }

  return(result)

}

Ellipsis can pass any number of parameters.