[R] can this sequence be generated easier?

[Bill.Venables at csiro.au]

Here ia an idea that might be useful to adapt

fixedSumCombinations <- function(N, terms) 
	if(terms == 1) return(N) else
	if(terms == 2) return(cbind(0:N, N:0)) else {
	X <- NULL
	for(i in 0:N) 
		X <- rbind(X, cbind(i, Recall(N-i, terms-1)))
	X
}

example:

> fixedSumCombinations(4, 3)
      i    
 [1,] 0 0 4
 [2,] 0 1 3
 [3,] 0 2 2
 [4,] 0 3 1
 [5,] 0 4 0
 [6,] 1 0 3
 [7,] 1 1 2
 [8,] 1 2 1
 [9,] 1 3 0
[10,] 2 0 2
[11,] 2 1 1
[12,] 2 2 0
[13,] 3 0 1
[14,] 3 1 0
[15,] 4 0 0

Bill Venables.

________________________________________
From: r-help-bounces at r-project.org [r-help-bounces at r-project.org] On Behalf Of pdb [philb at philbrierley.com]
Sent: 18 June 2011 14:34
To: r-help at r-project.org
Subject: [R] can this sequence be generated easier?

I have 'x' variables that I need to find the optimum combination of, with the
constraint that the sum of all x variables needs to be exactly 100. I need
to test all combinations to get the optimal mix.

This is easy if I know how many variables I have - I can hard code as below.
But what if I don't know the number of variables and want this to be a
flexible parameter. Is there a sexy recursive way that this can be done in
R?

#for combinations of 2 variables
vars = 2
for(i in 0:100){
for(j in 0:(100-i)){
...do some test i,j combination
}}

#for combinations of 3 variables
vars = 3
for(i in 0:100){
for(j in 0:(100-i)){
for(k in 0:100-(i+j)){
...do some test on i,j,k combination
}}}



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