[R] compositional data: percent values sum up to 1

[Liaw, Andy]

Eh?  The original message says it's the design matrix that is perfectly
collinear after the transformation, not the response.

I don't know much about this type of data, but seems like you could just fit
the model w/o intercept to eliminate the collinearity, no?  It's the
interpretation of the result that may be tricky, I think.

Andy


> -----Original Message-----
> From: Spencer Graves [mailto:spencer.graves at pdf.com]
> Sent: Monday, June 02, 2003 9:33 AM
> To: Christoph Lehmann
> Cc: Spencer Graves; r-help at stat.math.ethz.ch
> Subject: Re: [R] compositional data: percent values sum up to 1
> 
> 
> "glm" will do multinomial logistic regression.  However, if J 
> is large, 
> I doubt if that will do what you want.  If it were my 
> problem, I might 
> feel a need to read the code for "glm" and modify it to do 
> what I want. 
>   Perhaps someone else can suggest something better.
> 
> hth.  spencer graves
> 
> Christoph Lehmann wrote:
> > I want to do a logistic regression analysis, and to compare with, a
> > discriminant analysis. The mentioned power maps are my 
> exogenous data,
> > the dependent variable (not mentioned so far) is a diagnosis
> > (ill/healthy)
> > 
> > thanks for the interest and the help
> > 
> > Christoph
> > 
> > On Sun, 2003-06-01 at 21:01, Spencer Graves wrote:
> > 
> >>What are you trying to do?  What I would do with this 
> depends on many 
> >>factors.
> >>
> >>spencer graves
> >>
> >>Christoph Lehmann wrote:
> >>
> >>>again, under another subject:
> >>>sorry, maybe an all too trivial question. But we have 
> power data from J
> >>>frequency spectra and to have the same range for the data 
> of all our
> >>>subjects, we just transformed them into % values, pseudo-code:
> >>>
> >>>power[i,j]=power[i,j]/sum(power[i,1:J])
> >>>
> >>>of course, now we have a perfect linear relationship in 
> our x design-matrix,
> >>>since all power-values for each subject sum up to 1.
> >>>
> >>>How shall we solve this problem: just eliminate one column of x, or
> >>>introduce a restriction which says exactly that our power 
> data sum up to
> >>>1 for each subject?
> >>>
> >>>Thanks a lot
> >>>
> >>>Christoph
> >>
> >>______________________________________________
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> >>https://www.stat.math.ethz.ch/mailman/listinfo/r-help
> >
> 
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