 |
 |
I know I am likely to re-open a discussion about non-informative priors for precision parameters, but I would still value your help related to a more specific problem I have encountered. I am fitting a hierarchical model in which parameters are distributed according to a gamma distribution, parameterised by mu and tau as in the Bugs manual. I need to put some vague priors on mu and tau. I know that the parameters to be fitted should be positive and not very large but otherwise I have not other prior belief (or rather I do not want my belief in the parameters to influence the results). Choosing: ... phi1[i, k] ~ dgamma(tau1[k],mu1[k]) ... mu1[k] ~ dgamma(1.0E-3, 1.0E-3) tau1[k] ~ dgamma(1.0E-3, 1.0E-3) ... or similar leads to an extremely fat-tailed (and wiggly) distribution of a mean and variance of a phi1 and convergence problems. Any clues? Thanks in advance, Adam Kleczkowski -- Adam Kleczkowski [log in to unmask] (work), [log in to unmask] (teaching) [log in to unmask] (private) http://mathbio.com (work), http://kleczkowski.net (private) ------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list