Hierarchical prior for the regression coefficients


#1

Hi, I tried to specify a simple hierarchical prior for my model in brms but couldn’t figure out how to do it. Suppose I want to regress y onto x1 and x2 (simple linear regression, no group-level effects or anything). Denote the regression coefficients by b1 and b2. I would like to set prior N(0,tau) for both b1 and b2, so that also tau is treated as unknown (hyper)parameter for which I would like to place a prior (say half-t or half-Cauchy) and which should then be inferred.

Is this possible and how should I do it? I tried using the stanvar function but as far as I understood it cannot be used to declare new parameters, only variables that are passed in as data.


#2

With the exception of some specific cases (b1 and b2 relating to the same categoricl variable), I don’t see any build in option for this. But maybe there should be one? Feel free to open an issue on github if you like.


#3

Thanks for a prompt answer! I now created an issue in Github, as I think this would be a useful feature.