Efficient Sampling of Multinomial Processing Tree using NUTS?

Upon investigation the issue was installing Theano and having it ‘play nice’ with PyMC3 on Windows 10, rather than problems with the model itself.

Depending on whether I tried installing everything via conda, conda-forge (e.g. theano, m2w64-toolchain, mkl-service, etc), or manually installing MinGW for the g++ compiler (as suggested here), I variously encountered errors very similar to those described here and here. Typically the model would stall at 3.40% or so, regardless of the number of cores, chains, priors, inits.

My current solution is not ideal but working well, sampling within 15 seconds and yielding results similar to @nkaimcaudle (thanks btw - that looks correct as per the text!). I followed these instructions, setting up a virtual environment using somewhat older versions of Python and PyMC3 (both 3.5). EDIT: Actually, even this is only working with one core. Trying to add more throws this error :upside_down_face:.

I’ll keep trying to fix the issue in a separate virtual env (just came across another post which may be helpful) and will report back if I find any solutions, but setting things up on Windows 10 unfortunately remains a bit of a headache for now. Thank you thank you @junpenglao, and super excited for PyMC4!