search for: crru

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2012 Sep 12
7
multinomial MCMCglmm
...hat. 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...
2012 Sep 12
0
R-help Digest, Vol 115, Issue 12
...ace: 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 &...
2012 Nov 06
1
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 do...