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.
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
f
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 o
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