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

[Spencer Graves]

"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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