It seems that writing to a diagnostics file hasn’t quite been implemented for PyStan yet, so is there another way to get diagnostics about the sampler?
Raw values you can get with
fit.get_sampler_params()
Next release has pystan.diagnostics. It contains functions that will hint you if you have a problem with your model.
Is there a guide on how to interpret the statistics it returns? My divergence array is full of ones for instance, is this a count or a boolean? (I’m guessing it is bad either way).
This doesn’t use the new build in functions, but explains some of the interpretation of the diagnostics, https://betanalpha.github.io/assets/case_studies/pystan_workflow.html. More on divergences with corresponding R code (which is sufficiently easy to translate to Python) can be found at https://betanalpha.github.io/assets/case_studies/divergences_and_bias.html.
Is there any plan to integrate the stan_utility into PyStan?
It’s already merged.
See https://github.com/stan-dev/pystan/pull/433
To get it before 2.18 is released install from git
pip install git+https://github.com/stan-dev/pystan
What @ahartikainen. Note that I update the stan_utility functionality from time to time so the version in my case studies will always be the most up to date.
Yeah, sorry, I didn’t check if it was updated.
Oh, no worries. There hasn’t been any substantial change yet, but there will be at some point. I was just making the point that the diagnostics are still a matter of research and hence evolving, so while we’ll strive to keep the versions in the interfaces up to date the most advanced versions that I recommend will be in the case studies.
2 Likes