I am learning Bayesian Regression Modeling with Statistical Rethinking.
I want to try to write stancode from now on to learn some basics there and I think it is better than e.g. using the formula as you can do in brms because you have to specify everything explicitly.
However, I love the brms package and have my workflow with that. Is there a way to give brms just the stan file instead of the formula and fit the model? I know that is possible with rstan but I think brms has some functions that do not work with rstan that were part of my workflow.
If you have alternative options about how I should learn stan, feel free to suggest. My idea was to just now write those models that I can understand in stan and use brms with that.
brms provides its extra functionality by controlling how the models are written, so I don’t think there’s any way to feed a plain Stan model to brms and get the features out.
But what were those functions? Maybe there’s another way to solve this.
ok, thanks for letting me know. Yes there are defnitively alternatives. I am talking about extracting posterior samples and creating summaries etc. I had written some functions that used brms functions to achieve this. I will look up the same functions for rstan. Because the (I assume) rstan is the best way to go. Please correct me if I am wrong or there are better/smarter ways in the long run.
You could also check out the posterior package which you can find on the stan-dev github page.
Thanks Paul and bbales2,
I found the posterior package and I found all kinds of new developments that I was unaware of. I assume that for me as an R user cmdstanR is the way to go to be future proof.
@paul.buerkner and @bbbales2:
What is the easiest way to compute posterior means in “complicated” analysis with many interactions? Or other way to ask: Is there a similar function such as
posterior_linpred for cmdstanr or that has been implemented in the posterior package?
For many analyses I could do it manually but it can become cumbersome quickly with increasing complexity.