Using two for loops to fill one empty matrix by rows - r

Question

I'm trying to do a forecast analysis with some error measures. My question relates more to a technical Problem.
Here is a short example:
Im studying error measures regarding to the forecast length (h) and the k-step-forecast. I want to compare forecast lengths of 12, 18 and 24 months.
h<-c(12,18,24)
And for that lengths I'm comparing the 1-12 step ahead forecasts.
k <- c(1:12)
I've written two functions:
The first one (foo) is computing the hole code and the second one (forecast_analysis) is doing my forecast Analysis.
foo <- function(series, k, h){
Outfinal <- matrix(nrow = length(h)*length(k), ncol = 5)
for(i in 1:length(h)){
for(j in 1:length(k)){
Outfinal[j,] <- forecast_analysis(series,k[j],h[i])
}
}
return(Outfinal)
}
my Problem is, that I couldnt find a way to fill the Matrix by rows like this:
h k measure 1 measure 2 measure3 measure 4 measure 5
12 1
12 2
12 3
. .
. .
. .
24 10
24 11
24 12
So, first I want to fill the Matrix for a fixed value of h for all values of k. And then repeating this for all values of h. I hope ure understanding my Problem.
I know that apply functions would be more efficient here. But I'm not yet able to do so.

Answer 1

You can build a table of all h x k combinations plus a result using expand.grid.
This code should get you started
dummy_forecast <- function(h, k) 42
h<-c(12,18,24)
k <- 1:12 # no need for the c function here
combinations <- expand.grid(h = h, k = k, forecast = NA)
for (row in seq_along(combinations$h)) {
combinations[row, "forecast"] <-
with(combinations[row,], dummy_forecast(h, k))
}
If you return more than one value from your function, you need to assign to more than one column in combinations[row,...], but otherwise it should work.
Update
To handle a function that returns more than one value, do something like this:
dummy_forecast <- function(h, k) rep(42, 5)
result <- matrix(nrow = length(h) * length(k), ncol = 7)
combinations <- expand.grid(h = h, k = k)
for (row in seq_along(combinations$h)) {
result[row,] <- with(combinations[row,], c(h, k, dummy_forecast(h, k)))
}