[R] princomp() with missing values in panel data?
Prof Brian Ripley
ripley at stats.ox.ac.uk
Tue Jan 17 06:50:09 CET 2006
See ?na.exclude (on the same page as na.omit)
On Mon, 16 Jan 2006, ivo welch wrote:
> dear R wizards: the good news is that I know how to omit missing
> observations and run a principal components analysis.
> p= princomp( na.omit( dataset ) )
> p$scores[ ,1] # the first factor
> (where dataset contains missing values; incidentally, princomp(retailsmall,
> na.action=na.omit) does not work for me, so I must be doing something wrong,
See ?princomp: only the formula method has an na.action argument.
> the bad news is that I would like NA observations to be retained as
> NA, so that I can reinsert the factors into the data set:
> dataset$first.factor = p$scores[,1]
> there must be an elegant way of doing this. help appreciated.
> may I humbly suggest that in linear models, it would be intuitive if the
> default would be for NA's to be ignored in the model computations, and that
> the functions residuals and fitted (and similar, such as scores() ) to
> understand when a particular obs num should be NA?
There is no function scores().
> help, as always, appreciated.
> /ivo welch
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Brian D. Ripley, ripley at 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
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