djmuseR wrote:
>
> On Sun, Dec 26, 2010 at 4:18 AM, bbslover <dlu...@yeah.net> wrote:
>
>>
>> x: is a matrix 202*263, that is 202 samples, and 263 independent
>> variables
>>
>> num.compd<-nrow(x); # number of compounds
>> diss.all<-0
>> for( i in 1:num.compd)
>> for (j in 1:num.compd)
>> if (i!=j) {
>>
>
> Isn't this just X'X?
>
>> S1<-sum(x[i,]*x[j,])
>>
> Aren't each of S2 and S3 just diag(X'X)?
>
>> S2<-sum(x[i,]^2)
>>
> S3<-sum(x[j,]^2)
>> sim2<-S1/(S2+S3-S1)
>> diss2<-1-sim2
>> diss.all<-diss.all+diss2}
>>
>
> I tried
> s1 <- crossprod(x)
> s2 <- diag(s1)
> s3 <-outer(s2, s2, '+') - s1
> s1/s3
>
> This yields a symmetric matrix with 1's along the diagonal and quantities
> between 0 and 1 in the off-diagonal. Something like it could conceivably
> be
> used as a similarity matrix. Is that what you're looking for with sim2?
>
> I agree with Berend: it looks like a problem that could be easily solved
> with some matrix algebra. R can do matrix algebra quite efficiently,
> y'know...
>
> (BTW, I tried this on a 1000 x 1000 input matrix:
> system.time(myfunc(x))
> user system elapsed
> 0.99 0.02 1.02
>
> I expect it could be improved by an order of magnitude if one actually
> knew
> what you were computing... )
>
I did some more work along Dennis' lines
xtx <- tcrossprod(x)
xtd <- diag(xtx)
xzz <- outer(xtd,xtd,'+')
zz <- 1 - xtx/(xzz-xtx)
diss.all <- sum(zz)
this appears to give the desired result and it's quite a bit faster than my
alternative 2.
It would indeed be nice to know what is being computed.
Berend
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