[R-sig-ME] MCMCglmm prior specification

[Iker Vaquero Alba]

   Hi Jarrod,   Thanks a lot for your reply. I had actually found information about it in another post and wanted to "fix" my own question, but for some reason individual posts don't arrive to my email even if I have that option activated, so I couldn't reply to myself.   My question, then, would be: most of the times I see priors with just R and G elements, but not B. Is it not necessary to specify B? Also, if my model does not have random effects, then would it be enough with a prior for R element? 

   Thank you very much.   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




     De: Jarrod Hadfield <j.hadfield at ed.ac.uk>

CC: "r-sig-mixed-models at r-project.org" <r-sig-mixed-models at r-project.org> 
 Enviado: Lunes 12 de octubre de 2015 11:56
 Asunto: Re: [R-sig-ME] MCMCglmm prior specification
   
Hi,

R defines the prior for the residual covariance matrices. B specifies 
the prior for the `fixed' effects.

Cheers,

Jarrod




10:34:01 +0000 (UTC):



>    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
>
>
>     [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
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>



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