Certain authors have been reporting impressive shrinkage performance from incorporation of the so-called "horseshoe" (http://www.jmlr.org/proceedings/papers/v5/carvalho09a/carvalho09a.pdf) and "horseshoe plus" (http://arxiv.org/pdf/1502.00560v2.pdf) priors into their MCMC sampling.
I've seen a fair amount of attention to incorporating these into Stan programming, but I still prefer to use MCMCglmm at times, particularly with large groups. Has anyone successfully incorporated any of the horseshoe priors for usage in MCMCglmm, through parameter expansion or otherwise?
Warm regards,
Jonathan