question on MCMCglmm

Hi,

The prior for the fixed effects is (multivariate) normal, specified as:

prior=list(B=list(mu=mu, V=V))

where mu are your prior means, and V your prior (co)variances. The  
default is mu=0 and V = I*1e+10: depending on the scale of your data  
this is probably close to uniform.

The random effects also have a (multivariate) normal prior, determined  
by the estimated variances. You place a hyper-prior on these variances  
by specifying the G element in the prior.

Cheers,

Jarrod


Quoting emre karaman <emre_marmara2002 at yahoo.com> on Mon, 26 Mar 2012  
01:33:24 -0700 (PDT):

Dear Dr.,
For one-way anova model I assume a uniform distribution for overall  
mean, that is p(mu)=1, and a normal distribution for random effects.  
However, prior specification for
overall mean
is not clear, at least yet for me. Could you please tell the way to  
overcome this problem.
Best Wishes.?
	[[alternative HTML version deleted]]

The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.