How to pass matrix columns as parameters to an .apply function?

Question

I want to pass multiple parameters at once to a function, where these parameters are vectors contained in a matrix like this one:

> head(M, 3)
           [,1]      [,2]       [,3]
[1,]  1.3709584  1.304870 -0.3066386
[2,] -0.5646982  2.286645 -1.7813084
[3,]  0.3631284 -1.388861 -0.1719174

For example considering cor() the following line gives me what I want, but I don't want nesting.

> sapply(1:3, function(x) sapply(1:3, function(y, ...) cor(M[, x], M[, y])))
           [,1]       [,2]       [,3]
[1,]  1.0000000 -0.3749289  0.4400510
[2,] -0.3749289  1.0000000 -0.1533438
[3,]  0.4400510 -0.1533438  1.0000000

I thought outer() would be a candidate, since:

> outer(1:3, 1:3, function(x, y) x + y)
     [,1] [,2] [,3]
[1,]    2    3    4
[2,]    3    4    5
[3,]    4    5    6

But

corFun <- function(x, y) cor(M[, x], M[, y])
outer(1:3, 1:3, corFun)

won't work. mapply(corFun, M[, 1], M[, 2]) attempts won't work either.

I want to do xFun(corFun, M, arg) or even better xFun(cor, M, arg) that gives (like above):

           [,1]       [,2]       [,3]
[1,]  1.0000000 -0.3749289  0.4400510
[2,] -0.3749289  1.0000000 -0.1533438
[3,]  0.4400510 -0.1533438  1.0000000

where arg <- combn(1:3, 2) or arg <- t(expand.grid(1:3, 1:3)) .

Generally I'm wondering if there's an existing base R function something like xFun(FUN, ..., arg) that passes a parameter matrix arg with dim(arg)[1] == 2 column-wise to a function FUN = function(x, y) , or, perhaps, even more generally dim(arg)[1] == length(formals(FUN)) .

---

Data:

set.seed(42)
M <- matrix(rnorm(30), 10, 3)

Answer 1

outer is your function but you just need to Vectorize your corfun

outer(1:3, 1:3, Vectorize(corFun))
#           [,1]       [,2]       [,3]
#[1,]  1.0000000 -0.3749289  0.4400510
#[2,] -0.3749289  1.0000000 -0.1533438
#[3,]  0.4400510 -0.1533438  1.0000000

Answer 2

Another option would be combn

combn(1:3, m = 3, FUN = corFun)[,, 1]
#           [,1]       [,2]       [,3]
#[1,]  1.0000000 -0.3749289  0.4400510
#[2,] -0.3749289  1.0000000 -0.1533438
#[3,]  0.4400510 -0.1533438  1.0000000

The result however is an array, hence the [,, 1] .