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 <[EMAIL PROTECTED]> 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]] > >>> > >>> ______________________________________________ > >>> 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. > >>> > >> > >> ______________________________________________ > >> 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. > >> > > > > ______________________________________________ > > 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. > > > > -- > Brian D. Ripley, [EMAIL PROTECTED] > 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. > [[alternative HTML version deleted]] ______________________________________________ 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.