[R] multinomial MCMCglmm

2012-11-06 Thread Vaniscotte
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="multinomia

[R] Multinomial MCMCglmm

2012-11-06 Thread Vaniscotte.A
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",

[R] multinomial MCMCglmm

2012-10-09 Thread Vaniscotte Amélie
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 is a trapping data set, where the observation at each trap (1 or 0 for several species) have been aggregated per trapline (i.e. 25 traps). Therefore we

Re: [R] multinomial MCMCglmm

2012-10-07 Thread Ben Bolker
Vaniscotte gmail.com> writes: > > Dear all, > > I would like to add mixed effects in a multinomial model and I am trying > to use MCMCglmm for that. [snip] > > "ill-conditioned G/R structure: use proper priors if you haven't or > rescale data if you have" > > I guess that the problem com

[R] multinomial MCMCglmm

2012-10-06 Thread Vaniscotte
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 is a trapping data set, where the observation at each trap (1 or 0 for several species) have been aggregated per trapline (i.e. 25 traps). Therefore w

[R] multinomial MCMCglmm

2012-10-06 Thread Vaniscotte
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 is a trapping data set, where the observation at each trap (1 or 0 for several species) have been aggregated per trapline (i.e. 25 traps). Therefore w

[R] multinomial MCMCglmm

2012-10-06 Thread Vaniscotte
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 is a trapping data set, where the observation at each trap (1 or 0 for several species) have been aggregated per trapline (i.e. 25 traps). Therefore w

[R] multinomial MCMCglmm

2012-09-25 Thread Vaniscotte
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 is a trapping data set, where the observation at each trap (1 or 0 for several species) have been aggregated per trapline (i.e. 25 traps). Therefore w

[R] multinomial MCMCglmm

2012-09-25 Thread Vaniscotte Amélie
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 is a trapping data set, where the observation at each trap (1 or 0 for different species) have been aggregated per traplines (i.e sum over 25 traps). T

[R] multinomial MCMCglmm

2012-09-20 Thread Vaniscotte
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

[R] multinomial MCMCglmm

2012-09-12 Thread Vaniscotte
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

[R] multinomial MCMCglmm

2012-09-12 Thread Vaniscotte
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