Dear Prof Brian Ripley,

Would you also recommend some packages for non-binary data to do
variable and feature selection?

Thanks a lot!

Alex


On 6/12/07, Prof Brian Ripley <ripley@stats.ox.ac.uk> wrote:
>
> On Tue, 12 Jun 2007, Spencer Graves wrote:
>
> >      The problem with applying prcomp to binary data is that it's not
> > clear what problem you are solving.
> >
> >      The standard principal components and factor analysis models
> > assume that the observations are linear combinations of unobserved
> > "common" factors (shared variability), normally distributed, plus normal
> > noise, independent between observations and variables.  Those
> > assumptions are clearly violated for binary data.
> >
> >      RSiteSearch("PCA for binary data") produced references to 'ade4'
> > and 'FactoMineR'.  Have you considered these?  I have not used them, but
> > FactoMineR included functions for 'Multiple Factor Analysis for Mixed
> > [quantitative and qualitative] Data'
>
> AFAIK, that is not using 'factor analysis' in the same sense as e.g.
> factanal().
>
> Continuous underlying variables with binary manifest variables is part of
> latent variable analysis.  Package 'ltm' covers a variety of such models.
>
> But to begin to give advice we would need to know the scientific problem
> for which Ranga Chandra Gudivada is looking for a tool. Simon Blomberg
> mentioned ordination, but that is only one of several classes of uses of
> PCA (which finds a linear subspace that both has maximal variance within
> and is least-squares fitting to the data).
>
> >
> >      Hope this helps.
> >      Spencer Graves
> >
> > Josh Gilbert wrote:
> >> I don't understand, what's wrong with using prcomp in this situation?
> >>
> >> On Sunday 10 June 2007 12:50 pm, Ranga Chandra Gudivada wrote:
> >>
> >>> Hi,
> >>>
> >>>     I was wondering whether there is any package implementing
> Principal
> >>> Component Analysis for Binary data
> >>>
> >>>                                               Thanks chandra
> >>>
> >>>
> >>> ---------------------------------
> >>>
> >>>
> >>>     [[alternative HTML version deleted]]
> >>>
> >>> ______________________________________________
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> minimal,
> >>> self-contained, reproducible code.
> >>>
> >>
> >> ______________________________________________
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> >> PLEASE do read the posting guide
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> >> and provide commented, minimal, self-contained, reproducible code.
> >>
> >
> > ______________________________________________
> > R-help@stat.math.ethz.ch mailing list
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> > PLEASE do read the posting guide
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> > and provide commented, minimal, self-contained, reproducible code.
> >
>
> --
> 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 272866 (PA)
> Oxford OX1 3TG, UK                Fax:  +44 1865 272595
>
> ______________________________________________
> R-help@stat.math.ethz.ch 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.
>

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