R help - Nov 2012 - Multinomial MCMCglmm

Thanks for your answers Stephen and Ben,

I hope I am posting on the correct list now.

I managed so far to run the multinomial model with random effect with the
following command:

MCMCglmm(fixed=cbind(Apsy,Mygl,Crle,Crru,Miag,empty) ~
habitat:trait,random=~idh(trait):mesh,family="multinomial12",
data=dataA,rcov=~trait:units)

(where multiple responses are different species, 
Habitat the explanatory
variable and Mesh the random effect)

The main question I am facing now is:
Why the multinomial model fit does not provide by default a parameter
estimate for each response category but a unique one for all of them?  
I had to add interactions "trait:habitat" to get the same output as a
classical multinomial model... Therefore I wonder how the multinomial model
is implemented in this function... any idea?

The predict function is apparently not adapted for multinomial fit either
and need further improvements, right?

Best,

Am?lie



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Thanks for the answers to my previous post,

I hope I am posting on the correct list now.

I managed so far to run the multinomial model with random effect with 
the following command:

MCMCglmm(fixed=cbind(Apsy,Mygl,Crle,Crru,Miag,empty) ~
habitat:trait,random=~idh(trait):mesh,family="multinomial12",
data=dataA,rcov=~trait:units)

(where multiple responses are different species,
Habitat the explanatory
variable and Mesh the random effect)

The main question I am facing now is:
Why the multinomial model fit does not provide by default a parameter
estimate for each response category but a unique one for all of them?
I had to add interactions "trait:habitat" to get the same output as a
classical multinomial model... Therefore I wonder how the multinomial 
model is implemented in this function... any idea?

The predict function is apparently not adapted for multinomial fit 
either and need further improvements, right?

Best,

Am?lie V