Ah ha, that does work. What do you mean it isn't robust, though? I mean, obviously linear dependency structures in general are not stable under small perturbations...?
Or is it that it's platform dependent? Zhou On Fri, Feb 6, 2009 at 2:28 PM, Peter Dalgaard <p.dalga...@biostat.ku.dk> wrote: > Zhou Fang wrote: >> Hi, >> >> Okay, I have a n x p matrix X, which I know is not full rank. In >> particular, there may be linear dependencies amongst the columns (but >> not that many). What is a fast way of finding a linearly independent >> subset of the columns of X that will span the column space of X, in R? >> If it helps, I have the QR decomposition of the original X 'for free'. >> >> I know that it's possible to do this directly by looping over the >> columns and adding them, but at the very least, a solution without >> horrible slow loops would be nice. > > Have a look at stats:::Thin.col(), but beware that it isn't terribly robust. > >> Any ideas welcome. >> >> Zhou Fang >> >> ______________________________________________ >> 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. > > > -- > O__ ---- Peter Dalgaard Øster Farimagsgade 5, Entr.B > c/ /'_ --- Dept. of Biostatistics PO Box 2099, 1014 Cph. K > (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 > ~~~~~~~~~~ - (p.dalga...@biostat.ku.dk) FAX: (+45) 35327907 > > ______________________________________________ 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.
