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Not a duplicate of rollapply for two-dimensional arrays (R), but rather an elaboration upon it – what I actually want to do is slightly more complicated than described in that question. I hoped that any answer to that question would easily extend to a solution for my actual problem, but that unfortunately proved not to be the case.

For simple vectors we have

```> a <- c(1:4)
> a
[1] 1 2 3 4
> rollapply(a, 2, mean)
[1] 1.5 2.5 3.5
```

which is as it should be. While

`rollapply`
itself is limited to one-dimensional vectors, several very helpful answers such as this one by akrun allowed me to extend this to two-dimensional arrays in a multitude of ways.

Unfortunately, I am now stuck again, because I do not see how any of the answers generalize to higher dimensions than two (*). Taking an array

`b`

```> b <- array(rep(c(1:4),each=6), c(2,3,4))
> b
, , 1

[,1] [,2] [,3]
[1,]    1    1    1
[2,]    1    1    1

, , 2

[,1] [,2] [,3]
[1,]    2    2    2
[2,]    2    2    2

, , 3

[,1] [,2] [,3]
[1,]    3    3    3
[2,]    3    3    3

, , 4

[,1] [,2] [,3]
[1,]    4    4    4
[2,]    4    4    4
```

there should be some way to take means over a window-size of 2 to yield

```, , 1

[,1] [,2] [,3]
[1,]  1.5  1.5  1.5
[2,]  1.5  1.5  1.5

, , 2

[,1] [,2] [,3]
[1,]  2.5  2.5  2.5
[2,]  2.5  2.5  2.5

, , 3

[,1] [,2] [,3]
[1,]  3.5  3.5  3.5
[2,]  3.5  3.5  3.5
```

but I do not see how (obviously in real cases the sub-arrays would not consist of just repeating the same integer throughout the array, but would contain actual data).

Ideally, I would also like to be able to assign different weights to the various sub-arrays in the window for the purposes of the averaging, but I assume that would just be a matter of defining a custom function to apply.

(*) Perhaps there is an obvious way, but it’s late where I am and I’m not finding it.

Anonymous Asked question May 13, 2021