Hi Michael,

Thanks for that. The X1 and X2 are vectors are typically 1000 by 3
matrices, and hoping to scale up to much larger dimensions (say 20,000 by
3).

I do appreciate your help and seems like this is the best way to do this, I
was just wondering if I could squeeze out just a bit more performance,
thats all.

Anyway thanks again, much appreciated.

Thanks,
Sachin

On Fri, Nov 18, 2011 at 9:15 AM, R. Michael Weylandt <
michael.weylandt@gmail.com> wrote:

> I fail to see why you would need another idea: you asked how to
> multiply matrices efficiently, I told you how to multiply matrices
> efficiently.
>
> if you want to calculate X1-X2 times W times X1-X2, then simply do so:
>
> X1 <- matrix(1:6, 3)
> X2 <- matrix(7:12, 3)
> W = matrix(runif(9), 3)
>
> t(X1-X2) %*% W %*% (X1-X2)
>
> which gives
>
> 142.7789 142.7789
> 142.7789 142.7789
>
> You could squeeze out one iota more of speed with
>
> crossprod(X1-X2, W) %*% (X1-X2)
>
> to get the same result, but unless you are doing massive scale linear
> processing, I'm not sure it's worth the loss of clarity.
>
> I was only giving you a heads up on the sometimes confusing difference
> between matrix multiplication in MATLAB and in R by which a vector is
> not a 1d matrix and so does not require explicit transposition.
>
> Michael
>
>
> On Thu, Nov 17, 2011 at 4:35 PM, Sachinthaka Abeywardana
> <sachin.abeywardana@gmail.com> wrote:
> > I'm not quite sure of what you mean by not worry if it's 1d R matrices.
> X1
> > and X2 are both n by d matrices and W is d by d.
> >
> > Thanks for the help though. Any other ideas?
> >
> > Thanks
> > Sachin
> >
> > On Friday, November 18, 2011, R. Michael Weylandt
> > <michael.weylandt@gmail.com> wrote:
> >> The fastest is probably to just implement the matrix calculation
> >> directly in R with the %*% operator.
> >>
> >> (X1-X2) %*% W %*% (X1-X2)
> >>
> >> You don't need to worry about the transposing if you are passing R
> >> vectors X1,X2. If they are 1-d matrices, you might need to.
> >>
> >> Michael
> >>
> >> On Thu, Nov 17, 2011 at 1:30 AM, Sachinthaka Abeywardana
> >> <sachin.abeywardana@gmail.com> wrote:
> >>> Hi All,
> >>>
> >>> I am trying to convert the following piece of matlab code to R:
> >>>
> >>> XX1 = sum(w(:,ones(1,N1)).*X1.*X1,1);          #square the elements of
> >>> X1,
> >>> weight it and repeat this vector N1 times
> >>> XX2 = sum(w(:,ones(1,N2)).*X2.*X2,1);          #square the elements of
> >>> X2,
> >>> weigh and repeat this vector N2 times
> >>> X1X2 = (w(:,ones(1,N1)).*X1)'*X2;                 #get the weighted
> >>> 'covariance' term
> >>> XX1T = XX1';                                              #transpose
> >>> z = XX1T(:,ones(1,N2)) + XX2(ones(1,N1),:) - 2*X1X2;            #get
> the
> >>> squared weighted distance
> >>>
> >>> which is basically doing: z=(X1-X2)' W (X1-X2)
> >>>
> >>> What would the best way (for SPEED) to do this? or is vectorizing as
> >>> above
> >>> the best? Any hints, suggestions?
> >>>
> >>> Thanks,
> >>> Sachin
> >>>
> >>>        [[alternative HTML version deleted]]
> >>>
> >>> ______________________________________________
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> >>> https://stat.ethz.ch/mailman/listinfo/r-help
> >>> PLEASE do read the posting guide
> >>> http://www.R-project.org/posting-guide.html
> >>> and provide commented, minimal, self-contained, reproducible code.
> >>>
> >>
>

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