[R] Calculating subsets of row pairs using somthing faster than a for loop.

[Bernzweig, Bruce (Consultant)]

Hi all,

 

Situation:

 

 - I have two matrices each w/ 4 rows and 20 columns.

 

mat1 <- matrix(sample(1:500,80), ncol = 20, 

            dimnames=list(paste("mat1row", 1:4, sep=""), 

            paste("mat1col", 1:20, sep="")))

 

mat2 <- matrix(sample(501:1000,80), ncol = 20, 

            dimnames=list(paste("mat2row", 1:4, sep=""), 

            paste("mat2col", 1:20, sep="")))

 

 - Each column represents a value in a time series.

 

Q: What do I want:

 

   Calculate moving average correlations for each row x row pair:

 

   For each row x row pair I want 10 values representing moving average

   correlations for 10 sets of time-values:

 

   cor(mat1[1,1:10], mat2[1,1:10])

   cor(mat1[1,2:11], mat2[1,2:11])

   ...

   cor(mat1[1,11:20], mat2[1,11:20])

   cor(mat1[1,1:10], mat2[2,1:10])

   ...

   cor(mat1[4,11:20], mat2[4,11:20])

 

   Result would be a 16 (rows) x 10 (col) matrix matMA

 

      ma1, ma2, ..., ma10 for (mat1 row1) x (mat2 row1)

      ma1, ma2, ..., ma10 for (mat1 row1) x (mat2 row2)

      ...

      ma1, ma2, ..., ma10 for (mat1 row4) x (mat2 row3)

      ma1, ma2, ..., ma10 for (mat1 row4) x (mat2 row4) 

 

   I would like to be able to do this without using a for loop

   due to the slowness of that method.

 

   Is it possible to iterate through subsets w/o using a for loop?

 

Thanks,

 

- Bruce

 

      P

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