When I’m using the
Interpolated
method in pymc.distributions to build a customized prior for a simple Bayesian logistic regression problem (I’m pretty much following the tutorial here).
I obtained the following error
SamplingError: Initial evaluation of model at starting point failed!
Starting values:
{‘intercept_interval__’: array(nan), ‘coeffs_interval__’: array(nan)}Initial evaluation results:
{‘intercept’: nan, ‘coeffs’: nan, ‘Y_obs’: -inf}
Any idea what causes the model to starting at nan? I’m using the default NUTS sampler btw.