So I have noticed that the
circular transform provided by PyMC3 has a zero-valued Jacobian. Wouldn’t this pose an issue for differentiation-based inference like NUTS and ADVI?
I recall having had some issues with NaN’s when using a mixture of VonMises distributions (An extended model of the one presented in NaN occured in optimization in a VonMises mixture model), which were solved when I used a mixture of Normals instead.
Could this be the potential cause?
Thank you in advance!