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.abeyward...@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]] > > ______________________________________________ > R-help@r-project.org mailing list > 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. > ______________________________________________ R-help@r-project.org mailing list 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.
