There is something I want to do which I believe should be easily achieved with rollapply, but I am having some trouble.
For simple vectors we have
> a <- c(1:10)
> a
[1] 1 2 3 4 5 6 7 8 9 10
> rollapply(a, 2, mean)
[1] 1.5 2.5 3.5 4.5 5.5 6.5 7.5 8.5 9.5
which is as it should be. But problems arise for higher dimensions
> b <- array(c(1:6), c(2,3))
> b
[,1] [,2] [,3]
[1,] 1 3 5
[2,] 2 4 6
> rollapply(b, 2, mean)
[,1] [,2] [,3]
[1,] 1.5 3.5 5.5
which is fine if I want to apply over columns - but surely there must also be some way to apply over rows instead and get
[,1] [,2]
[1,] 2 4
[2,] 3 5
The rollapply function offers no way to do this that I can see.
We can simply use apply with MARGIN = 1 to loop over the rows and apply the rollapply. The MARGIN can be adjusted for higher dimensions as well i.e. it is more general solution
t(apply(b, 1, function(x) rollapply(x, 2, mean)))
-output
# [,1] [,2]
#[1,] 2 4
#[2,] 3 5
Or use dapply from collapse
library(collapse)
dapply(b, FUN = function(x) rollapply(x, 2, fmean), MARGIN = 1)