Hi,

I've been working up a dataset of soils and vegetation and I'd like to run a
multinomial regression model with this data.  The data includes six possible
outcomes (vegtation types) and anywhere from 1 to 5 independent predictors
(nutrient and hydrological properties).  I've been looking at the mlogit
package, globaltest (bioconductor) package, and glm modeling capabilities.

Using the globaltest package I came up with a solution, but have some
reservations.

Which package and function is more commonly used for ecological
investigations of this kind?

How can I develop a plot illustrating the probabilities of each of the six
response vegetation types for a given concentration of nutrients (the
independent predictors) ?

Eventually, I will add several predictors to this model. Is there a method
that I can use that will allow me to use multiple predictors and multiple
responses ?

If anyone really wants to see the code I'm using, I'll have to get it from
my office tomorrow.

Thanks
Steve

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