[R] logistic regression or discriminant analysis ?

Daniel Amorèse Daniel.Amorese at geos.unicaen.fr
Mon May 27 10:10:49 CEST 2002

Le 2002.05.24 16:55, Marc R. Feldesman a écrit :
> At 01:49 AM 5/24/2002, Daniel Amorèse took a glob of electronic fairy
> dust, 
> mushed it together in odd and bizarre ways, and ruminated:
>  >Le 2002.05.23 19:38, Marc Feldesman a écrit :
>  >> At 06:25 PM 5/23/2002 +0200, Daniel Amorèse wrote:
>  >> >Hello,
>  >What I have done: the correlation matrix tells me that many
>  >variables are correlated. Thus, I performed a lda using only 5
>  >variables (this selection is arbitrary performed among uncorrelated
>  >variables). The graphical output shows points clouds that are not
>  >circular: this result may suggest difference in covariance
>  >matrices, hence lda seems not to be the more suitable method for
>  >separating groups.
> Elliptical point clouds do not, in themselves, suggest unequal covariance
> structures.  If the major axes of the ellipses are all oriented in the
> same 
> direction and are more-or-less parallel, you don't have much evidence of 
> unequal covariance structure.  Unless the covariance structures are
> really 
> different, I've never seen much improvement using quadratic discriminant 
> analysis.  The problem with quadratic discriminant analysis, in my 
> experience, is that it is very difficult to interpret the results in the 
> context of the variables producing the group separations.

Ok, the elliptical point clouds I obtain are not oriented in the same
so I should give up with lda or qda

> I'd strongly recommend Professor Ripley's "Pattern Recognition and Neural
> Networks" (Cambridge University Press, 1996), as well as Hastie, 
> Tibshirani, and Friedman's "The Elements of Statistical Learning" (2001, 
> Cambridge University Press).  Both will help you considerably with your 
> problem.

Thanks, for these references. What a pity the library of my university
seems to 
be allergic to english-written books
> I also agree with Jon Baron that clustering techniques may be appropriate
> here.

Ok, my ideas about this kind of approach are confused (I do not need
because my groups are already defined).
Some people told me about solving my problem using multinom() and

>  >Perhaps, qda should be used ?
>  >or logistic regression ? (this last method seems to be the more
>  >robust, independent to data properties).
>  >I know qda(), lda() or multinom() do not perform stepwise analysis,
>  >but, what I hope, is that some outputs from these functions can
>  >help in the selection of the most discriminatory variable subset.
>  >Thanks again for your help.
> D. Amorese
> Dr. Marc R. Feldesman
> Professor and Chairman
> Anthropology Department - Portland State University
> email:  feldesmanm at pdx.edu
> email:  feldesman at attglobal.net
> fax:    503-725-3905
> "Sometimes the lights are all shining on me, other times I can barely
> see,
> lately it's occurred to me, what a long strange trip it's been..."  Jerry
> &
> the boys
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