Hi,

I am trying to do a Cross Validation of Poisson models adjusted by MCMCglmm
package. Data were split randomly into three disjoint folds.
Using, for example, folds 1 and 2 for training, now I would like to predict
observations on fold 3.
I have some doubts about MCMCglmm:

First: Solutions for fixed and random effects are in the log scale, am I
correct? How can I obtain them on the response scale?
Solution_Response_scale = exp(Solution_log_scale) ?

Second: I saw that the first level of each fixed effect does not appear on
"model$Sol". Was this level`s solution setted to 0 and the others expressed
as deviation of it? How can I deal with this when predicting observations?

Third: When my observations have 0 as a response, how does the MCMCglmm deal
with it when it does log(observation)?


-- 
*Denise*

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