[R] Constrained, multiple response statistics

Jonathan Greenberg greenberg at ucdavis.edu
Wed Apr 8 22:19:11 CEST 2009


Hmm, it LOOKS like mvpart may be along the lines of what I want, but is 
mvpart a nominal classification tree, or can it handle multiple, 
continuous response variables as well?

--j

Gene Leynes wrote:
> This sounds very similar to what I've been working on, but I'm not 
> sure without an example.
>
> My solution has been to use an optimization that normalizes inside the 
> objective function.  The betas that are provided by optim are not 
> normalized, however since they were normalized inside the objective 
> function, normalizing them after the fact mirrors the internal 
> workings of the objective function.
>
> see this example:
> http://markmail.org/message/ze5237m6gbgvvvyf
>
> Still, after looking at several statistical packages, and considering 
> the thoughtful responses from my post, I think that there must be a 
> better way using existing models, so I've been looking at other 
> packages / models.
>
> On Tue, Apr 7, 2009 at 6:10 PM, Jonathan Greenberg 
> <greenberg at ucdavis.edu <mailto:greenberg at ucdavis.edu>> wrote:
>
>     R'ers:
>
>       I was hoping I could get some direction on this.  I have a
>     dataset of the form:
>
>     Y1,Y2,...,YM = f(X1,X2,...,XN), where N is >>> M
>
>     The response data (Y1,Y2,...,YM) is frequency data, such that the
>     sum of all Yi = 1.0.  Both Xj and Yi are continuous variables.
>
>     I'm trying to figure out the best approach(es) to solving for the
>     model f() -- any ideas?  I could solve each Y one at a time, but
>     the lack of constraint worries me, and I'm pretty sure that
>     normalizing the data afterwards to sum to 1.0 is not going to work
>     out properly.  Thoughts?  I've never worked with multiple response
>     statistics before, so I'm mostly trying to get some pointers on
>     where to begin investigating...
>
>     --j
>
>     -- 
>
>     Jonathan A. Greenberg, PhD
>     Postdoctoral Scholar
>     Center for Spatial Technologies and Remote Sensing (CSTARS)
>     University of California, Davis
>     One Shields Avenue
>     The Barn, Room 250N
>     Davis, CA 95616
>     Cell: 415-794-5043
>     AIM: jgrn307, MSN: jgrn307 at hotmail.com
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>
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