Yes, apparently I am having trouble reading today! I saw "Principal Coordinates Analysis" on the MDS wikipedia page, and my brain interpreted it as "Principal Components Analysis", and I went in the completely wrong direction. Sorry about that.
Derek On Jan 31, 2013, at 2:36 PM, Jean Véronis wrote: > Thanks for taking the time! In the meanwhile I checked PDL::Transform and > arrived at the same conclusion… > > I know Maggies's module -- PDL::Stats::Kmeans is the step in my chain > (clustering on the reduced matrix). However PCA is not the same a PCoA… If > don't think that exists under PDL or more generally for perl. I have a little > hope with R, since Rserve can quite speed up things > (http://www.rforge.net/Rserve/), and someone just started a pelr lint > (http://search.cpan.org/~djunkim/Statistics-RserveClient-0.01/lib/Statistics/RserveClient.pm). > We'll see… > > > Le 31 janv. 2013 à 22:27, Derek Lamb <[email protected]> a écrit : > >> OK, with this information I can tell you that PDL::Transform is probably not >> what you want--that does coordinate transforms (I was interpreting your >> question as in, "can I scale things (images, coordinates, etc) in multiple >> dimensions"). Thank you for the MDS wikipedia link. >> >> PCA might be a better search term. Look at Maggie's PDL::Stats module, >> which contains PDL::Stats::GLM. That includes some PCA routines. >> >> I don't know that GSL does PCA explicitly, but it should handle the >> eigenvalue or SVD portions of PCA just fine. There are some PDL::GSL:: >> modules but I don't think they include the eigen calculations. >> >> PDL::Slatec has the 'eigsys' function which may also be helpful. >> >> PDL::MatrixOps has the eigens. These last two I found by doing >> >> $pdldoc -a eigen >> >> from the command line after PDL was installed. >> >> There is a general R/Splus <--> Perl package here: >> http://www.omegahat.org/RSPerl/ but it has not been updated in many years, >> and I have never used it. >> >> best, >> Derek >> >> >> On Jan 31, 2013, at 1:52 PM, Jean Véronis wrote: >> >>> Thanks Derek, I am going to check PDL::Transform right away. >>> >>> My need is to reduce dimensionality on large distance matrices. For this is >>> use multidimensional scaling >>> (http://en.wikipedia.org/wiki/Multidimensional_scaling) by calling R from >>> perl (cmdscale function : >>> http://stat.ethz.ch/R-manual/R-patched/library/stats/html/cmdscale.html). >>> >>> It's perfectly fine, expect in terms of performance, since at the moment I >>> didn't find any better way than use Statistics:R, which basically passes >>> data through stdin/stdout. When it comes to huge matrices, it is extremely >>> inefficient. Hence my question. >>> >>> I tried to google "pdl multidimensional scaling", "gsl multidimensional >>> scaling", "perl multidimensional scaling", and all possible variants >>> involving "pcinipal coordinates analysis", "PCoA", with no success. >>> >>> Many thanks, again. >>> --j >>> >>> Le 31 janv. 2013 à 21:41, Derek Lamb <[email protected]> a écrit : >>> >>>> Hi Jean, >>>> >>>> The best hint I can provide based on the extremely limited information you >>>> have given is PDL::Transform. >>>> >>>> You might get a better response if you describe what you are trying to do >>>> in more than one sentence, what you have tried, whether you are new to PDL >>>> or Perl or are already using one or both, and what documentation you have >>>> looked at. >>>> >>>> best, >>>> Derek >>>> >>>> On Jan 31, 2013, at 1:24 PM, Jean Véronis wrote: >>>> >>>>> Hi all, >>>>> >>>>> I am looking for a multidimensional scaling package. >>>>> Any hint would be appreciated. >>>>> >>>>> Many thanks >>>>> --j >>>> >>> >> >
_______________________________________________ Perldl mailing list [email protected] http://mailman.jach.hawaii.edu/mailman/listinfo/perldl
