On Apr 9, 2012, at 3:17 PM, Kerapi wrote:
Hi!,
I'm really hoping someone out there will be able to help me.
I recently started my MSc dissertation on Population Projection
Matrices, which has been going well until now. I am trying to set-up
a general script that does a pairwise comparison of all elements in
my matrices.
So for example, given that I have the following matrix S:
S
[,1] [,2] [,3]
[1,] 0.00000 0.007361183 0.0001634936
[2,] 13.88458 0.353988378 0.0000000000
[3,] 0.00000 16.086367098 0.3572819557
I'd like to create a matrix SA for each element in my matrix
compared to another element like so:
SA
S-[1,1]
[,1] [,2] [,3]
[1,] [1,1]-[1,1] [1,2]-[1,1] [1,3]-[1,1]
[2,] [2,1]-[1,1] [2,2]-[1,1] [2,3]-[1,1]
[3,] [3,1]-[1,1] [3,2]-[1,1] [3,3]-[1,1]
Try this:
kS <- -1*kronecker(c(S),S, "-")
dim(kS) <- c(3, 3, 3, 3)
The row number is the thrid dimension and the col nimber is the second
dimension. If you want them to be rearrange to be in the ( r,c) order
you can use aperm.
> kSr <- aperm(kS, c(1, 4, 2, 3))
#The zero entires were used because I could easily tell what a correct
answer should be.
> kSr[,,3,1]
[,1] [,2] [,3]
[1,] 0.00000 0.007361183 0.0001634936
[2,] 13.88458 0.353988378 0.0000000000
[3,] 0.00000 16.086367098 0.3572819557
> kSr[,,1,1]
[,1] [,2] [,3]
[1,] 0.00000 0.007361183 0.0001634936
[2,] 13.88458 0.353988378 0.0000000000
[3,] 0.00000 16.086367098 0.3572819557
> kSr[,,2,3]
[,1] [,2] [,3]
[1,] 0.00000 0.007361183 0.0001634936
[2,] 13.88458 0.353988378 0.0000000000
[3,] 0.00000 16.086367098 0.3572819557
Test a non-zero entry
> kSr[,,2,2]
[,1] [,2] [,3]
[1,] -0.3539884 -0.3466272 -0.353824884
[2,] 13.5305916 0.0000000 -0.353988378
[3,] -0.3539884 15.7323787 0.003293578
> S - S[2,2]
[,1] [,2] [,3]
[1,] -0.3539884 -0.3466272 -0.353824884
[2,] 13.5305916 0.0000000 -0.353988378
[3,] -0.3539884 15.7323787 0.003293578
> sapply(1:3, function(rw) sapply(1:3,
function(cl) identical(S-S[rw,cl], kSr[,,rw,cl] )) )
[,1] [,2] [,3]
[1,] TRUE TRUE TRUE
[2,] TRUE TRUE TRUE
[3,] TRUE TRUE TRUE
--
David.
S-[1,2]
[...]
S-[1,3]
[...]
... and so on
The aim is to be able to prove existing rules and trends across
matrix dimensions.
For example, I've been trying to test whether the first line of
values decreases or remains the same from column 1 to the
penultimate column: S[1,j] >= S[1,l>j]
The last thing I tried was:
M<-Matlab2R("[0 24.724 1377.48;0.029328 0.26 0;0 0.014 0.78]")
w <- abs(Re(eigen(M)$vectors[,1]))
v <- abs(Re(eigen(t(M))$vectors[,1]))
w <- w/sum(w)
v <- v/(t(v)%*%w)
S <- (v%*%t(w))/as.vector(t(v)%*%w)
S
n<- length(S)
M.comp <- array(S,dim=c(n,n,n,n))
for (i in 1:n) {
for (j in 1:n) {
for (k in 1:n) {
for (l in 1:n) {
poscompa[1,3,1,j-1] <- S[i,j]<=S[k,l] # if=1, then TRUE and if=0,
then FALSE
}}}}
M.comp
sum(poscompa[1,3,1,1:n]) # should give me the value for n. I know
this doesn't test it accurately, but first I need to get the loops
to work right.
I'm getting an array of errors such as "can't find function poscompa
(or compa)", "subscripts out of range" or "type of closure not
valid" regardless of what I try. Using COMPAR (poscompa and compa)
was the last recommendation I got, but I'm starting to wonder if
there might be other ways to go about this. All out-of-the-box ideas
I've come up with and tried haven't gotten me much farther. I've now
practically exhausted my creative thinking, and I'm becoming very
frustrated. I'd really like to get this script going since my
current one would make my life hell for large populations (60x60
population matrices).
Any ideas on how I could move forward?
Many, many thanks!
Marta
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David Winsemius, MD
West Hartford, CT
______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
