Dear all,
I would like to add mixed effects in a multinomial model and I am trying
to use MCMCglmm for that.
The main problem I face: my data set consits of a trapping data set,
where the observation at eah trap (1 or 0 for each species) have been
aggregated per traplines. Therefore we have a proportion of
presence/absence for each species per trapline.
ex:
ID_line mesh habitat Apsy Mygl Crle Crru Miag Miar Mimi Mumu Misu Soar
Somi
11 028S6A 28 copse 2 0 0 0 0 0 0 0 0
0 0
12 028S6B 28 copse 1 1 0 0 0 0 0 0 0
0 0
13 028S6C 28 hedge 2 0 0 4 0 0 0 0 0
0 0
14 028S6D 28 hedge 1 0 0 7 0 0 0 0 1
0 0
15 028S6E 28 hedge 7 0 0 1 0 0 0 0 0
0 0
empty
11 28
12 28
13 24
14 21
15 22
When I run the following:
> test1 <-
MCMCglmm(fixed=cbind(Apsy,Mygl,Crle,Crru,Miag,Miar,Mimi,Mumu,Misu,Soar,Somi,empty)~habitat,random=~mesh,family="multinomial12",data=metalSmA[,c(2,9,23:34)],rcov=~us(trait):units)
I got some error when running regarding the variance structure:
> "ill-conditioned G/R structure: use proper priors if you haven't or
rescale data if you have"
I guess that the problem comes from the nature of my observation whih
are frequencies rather than 0/1 per unit
Does someone know if a multinomial model fitted with MCMCglmm can
handdle those frequencies table and how to specify the good G/R variance
structures?
Regards
Amélie Vaniscotte
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