A fistful of Stan case studies: divergences and bias, identifying mixtures, and weakly informative priors

Following on from his talk at StanCon, Michael Betancourt just wrote three Stan case studies, all of which are must reads:

Reproducible R scripts

They all come with fully reproducible knitr scripts to run in RStan. The same lessons hold for the other interfaces, so don’t let the R put you off.

A spectator sport

It was particularly fun sitting in the office the day Michael went and figured out all the mixture modeling properties. It followed on from one of our Stan meetings and some of my own failed experiments.

Publish or perish

It’s really a shame that this kind of methodological study is so hard to publish, because all three of these deserve to be widely cited. Maybe Andrew has some ideas of how to turn these into “regular” papers. The main thing journal articles give us is a way to argue that we got research results from our research grants. Not a small thing!

Other case studies

We have a bunch of case studies up and are always looking for more. The full list and instructions for submitting are on the Stan case studies page.

Getting information out of the posterior fit object in R

And in case you didn’t see it, Jonah wrote up a guide for how to extract the kind of information you need for extracting information from a Stan fit object in R.