R: calculating with different matrices - r

Question

I am using the following packages:
library("quantmod")
library("PerformanceAnalytics")
library("termstrc")
Data:
AAA <- matrix(sample(30), ncol = 10)
BBB <- matrix(sample(30), ncol = 10)
CCC <- matrix(sample(30), ncol = 10)
with
print(AAA)
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 28 18 16 10 20 21 23 27 5 6
[2,] 19 22 24 13 17 14 15 30 4 8
[3,] 1 25 11 2 29 9 3 7 12 26
> print(BBB)
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 26 22 24 21 23 25 11 17 8 13
[2,] 14 18 16 28 12 1 10 6 20 15
[3,] 9 4 30 7 5 27 2 3 19 29
> print(CCC)
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 6 29 9 24 26 10 12 21 5 22
[2,] 14 4 28 19 8 23 20 27 16 1
[3,] 7 17 13 18 30 2 3 15 11 25
Now I have the following problem:
There are 3 matrices (AAA, BBB and CCC), these matrices have all the same nummer of observations (3 obs. and 10 var.).
I calculated the min- & max-position for each row or observation in "AAA" (min/max for time t).
Calculated the following:
maxAAA_pos <- max.col(AAA)
minAAA_pos <- max.col(-AAA)
Result:
> print(maxAAA_pos)
[1] 1 8 5
> print(minAAA_pos)
[1] 9 9 1
The position of these min/max variables are telling me now which variable I have to take from the matrices BBB and CCC to calculate the following (example for the 1 observation):
Ft = variable from BBB at time t
St+1 = variable from CCC at time t+1
Result_max = (Ft / St+1) - 1
Result_min = 1 - (Ft / St+1)
My problem now is to select "Ft" and "St+1", which are given from the positions min/max variables from AAA and in the vector maxAAA_pos and minAAA_pos at time t.
This means the calculation should look like this for t=1 or the first observation:
Result_max = (26 / 14) - 1
Result_min = 1 - (8 / 16)
Thanks in advanced!

Answer 1

I found a solution, maybe the way is a bit complicated, but it works....
> AAA <- matrix(sample(30), ncol = 10)
> BBB <- matrix(sample(30), ncol = 10)
> CCC <- matrix(sample(40), ncol = 10)
>
> print(AAA)
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 27 12 15 5 3 25 16 28 11 19
[2,] 4 10 14 2 17 21 13 22 24 26
[3,] 23 1 9 30 18 6 7 29 20 8
> print(BBB)
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 1 20 3 23 2 8 17 19 22 15
[2,] 16 26 4 30 6 10 13 7 24 27
[3,] 18 28 5 11 21 9 12 29 25 14
> print(CCC)
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] 17 29 11 28 21 39 25 34 1 37
[2,] 36 8 5 19 6 26 33 32 14 3
[3,] 15 16 2 27 22 35 30 40 7 9
[4,] 20 4 12 23 31 24 10 18 38 13
>
>
> maxAAA_pos <- max.col(AAA)
> minAAA_pos <- max.col(-AAA)
>
>
> print(maxAAA_pos)
[1] 8 10 4
> print(minAAA_pos)
[1] 5 4 2
>
>
> pos_AAAmax <- cbind(1:3, maxAAA_pos)
> pos_AAAmin <- cbind(1:3, minAAA_pos)
>
>
> returnmax <- function(Ft, St) {
+ (Ft/St)-1
+ }
>
> returnmin <- function(Ft, St) { 1-(Ft/St)}
>
> returnmax(BBB[pos_AAAmax], CCC[cbind(pos_AAAmax[ ,1]+1, maxAAA_pos)])
[1] -0.4062500 2.0000000 -0.5217391
> returnmin(BBB[pos_AAAmin], CCC[cbind(pos_AAAmin[ ,1]+1, minAAA_pos)])
[1] 0.6666667 -0.1111111 -6.0000000