Hi Stanimals,

I am trying to follow the logic and derivation behind the idea to put a prior on R^2 for linear regression models. I am trying to write a step by step derivation to fully comprehend it.

I have to admit that I struggle a bit with the current description/derivation in the prior section of this vignette for rstanarm. In particular the identity of \theta relating it to \rho_k. I see how this works for the single variable case (best linear predictor interpretation of OLS) but not for the multiple regression case…

Is there an extended version of the vignette available somewhere, or any relevant literature pointers or derivations?

Otherwise I would ask my questions here…