Re: [R] qr and Moore-Penrose

Prof Brian Ripley (ripley@stats.ox.ac.uk)
Wed, 30 Jun 1999 15:12:25 +0100 (BST)

Message-Id: <199906301412.PAA17620@toucan.stats.ox.ac.uk>
Date: Wed, 30 Jun 1999 15:12:25 +0100 (BST)
From: Prof Brian Ripley <ripley@stats.ox.ac.uk>
Subject: Re: [R] qr and Moore-Penrose
To: ripley@stats.ox.ac.uk, hothorn@amadeus.statistik.uni-dortmund.de

> Date: Wed, 30 Jun 1999 15:44:58 +0200 (MET DST)
> From: Torsten Hothorn <hothorn@amadeus.statistik.uni-dortmund.de>
> To: Prof Brian Ripley <ripley@stats.ox.ac.uk>
> cc: r-help@stat.math.ethz.ch
> Subject: Re: [R] qr and Moore-Penrose
>
>
> > What is a correct result, by the way? There are infinitely many solutions
> > for the regression of y on X, and the Moore-Penrose one is just one choice
> > (that assumes that the coefficients are somehow comparable).
>
> hm, 1.5, -0.5, 0.5, 1.5 should be a unique solution to Xb = y (with
> minimal 2-norm).

And my point was `what has `minimal 2-norm' got to do with this'?
Regression coefficients are not necessarily in the same units: they are
not in a Euclidean space. There are lots of other solutions with
claims to be reasonable, including those which use just `rank' of the
columns. qr gives one of the latter.

-- 
Brian D. Ripley,                  ripley@stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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