[R-sig-ME] No residual variance using MCMCglmm

[Céline Teplitsky]

Dear all,

I have recently bumped twice in the same issue running glmm in MCMCglmm: 
the posterior distribution of residual collapses on 0. While I have 
often seen it for other effects (e.g ID) and interpreted it as evidence 
of non existence / non significance of these effects, I can not get why 
residual variance would not be well defined.

More specifically, with priors V=1, nu=0.02, I was trying to estimate 
additive genetic variance in age at first breeding. I first tried a 
Poisson distribution and the posterior distribution of the residual 
looked more or less ok, although not perfectly bell shaped. Then I 
thought as age at first breeding could not be zero, that a zero 
truncated Poisson might be better but then the posterior distribution of 
residual variance totally collapses on zero. As I thought it could be 
due to over parametrisation, I rerun the model with only intercept  but 
results were the same.

Is it a problem with the variables distributions not really fitting the 
distribution I'm specifying? Any help would be greatly appreciated!

Many thanks in advance

Celine

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Celine Teplitsky
UMR 7204 - CESCO
Département Ecologie et Gestion de la Biodiversité
CP 51
55 rue Buffon 75005 Paris

Webpage : http://www2.mnhn.fr/cersp/spip.php?rubrique96
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