?? Hello everyone,
?? I am reading a lot of documentation at the moment about prior specification in MCMCglmm, and there is still something I have not very clear. According to some sources, there are mainly two elements to take into account when defining a prior:?? - An R structure that needs to be specified for each fixed effect. And
?? - A G structure for each random effect.
?? However, in other sources another element, B, is introduced as well, which refers to fixed effects too. In Jarrod's Course Notes, I see that both R and B have to do with fixed effects: R specifies V and nu arguments for the variance, and B specifies V and mu elements for the mean.
??
?? My confusion comes from the fact that almost every time I see an example of a prior, it just has two elements, R (for fixed effects) and G (for random effects). Why is this? Is it not so important to define a prior for the mean? Is it enough with a prior specification for the variance of fixed effects and another one for all the random effects?
?? Thank you very much in advance.?? Iker
?
__________________________________________________________________
?? Iker Vaquero-Alba
?? Visiting Postdoctoral Research Associate
?? Laboratory of Evolutionary Ecology of Adaptations
?? Joseph Banks Laboratories
?? School of Life Sciences
?? University of Lincoln?? Brayford Campus, Lincoln
?? LN6 7DL
?? United Kingdom
?? https://eric.exeter.ac.uk/repository/handle/10036/3381