This is user error: that fit has class c("mlm", "lm") and
you should
be calling summary() on it, which will dispatch the mlm method.
For multiple-response linear models, there is also summary.manova.
On Wed, 30 Mar 2011, Stefan Schlager wrote:
> Dear all,
>
> I just stumbled upon the fact, that when I perform a regression on
> multivariate responses, that are not centred, I get a ricilulously high
> R-squared value. After reading the code of summary.lm, I found a bug in the
> function summary.lm:
>
> mss is calculated by:
> mss <-sum((f - mean(f))^2) - where f are the fitted values.
>
> This works only for a single response variable, because otherwise the
matrix
> containing the fitted values is scaled by a scalar. replacing
> this with:
> mss <- scale(f,scale=FALSE) solved the problem for me.
>
> Example for bug:
> response<-cbind(rnorm(500)+1000,rnorm(500)+300)
> predictor<-rnorm(500)
> fit<-lm(response ~ predictor)
> summary.lm(fit) now reports a R^2 value of 1!!!
>
> Please correct me, if I'm wrong
>
> Stefan
>
> Stefan Schlager M.A.
> Anthropologie
> Medizinische Fakult?t der der Albert Ludwigs- Universit?t Freiburg
> Hebelstr. 29
>
> 79104 Freiburg
>
> Anthropology
> Faculty of Medicine, Albert-Ludwigs-University Freiburg
> Hebelstr. 29
> D- 79104 Freiburg
>
> phone +49 (0)761 203-5522
> fax +49 (0)761 203-6898
>
>
>
> On 30/03/11 13:54, r-help-request at r-project.org wrote:
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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)
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