Hi there,
I understand that PyMC3 does an automatic imputation of missing data. I guess this cannot be an option that you can switch off because the code would crash because of these missing values and the alternative is to mask them.
I wonder whether the automatic imputation is also done for the posterior predictive check (sample_posterior_predictive and fast_sample_posterior_predictive)?
The reason for the question is that I’ve been considering adding some deterministic variables to the trace a posteriori (post-inference) to do the posterior predictive check on them. This would prevent me from adding them to the model, since they are not useful for the inference solution and since they take a lot of memory.
Cheers,
MV
