Hi,
There are various reasons why Bad initial energy can happen. Have you tried the solutions in our FAQ?
A few quick suggestions related to this:
- Make sure your data are standardized somehow if they are on a wide scale.
- Make sure your priors are not too wide, i.e informative enough – here are good practices on choosing priors. In general, I wouldn’t advice setting your priors with the data’s mean and std. First, this can force the sampler to start in a region of low curvature. Second, you’re using the data twice: once to set the priors, and another time to update them. However, the priors encode the scientific information you have before seeing any data.
- Make sure there are no inappropriate NaNs somewhere – you’ll find more details in the linked FAQ.
- Finally, you don’t have to specify
shapewhen the random variable is one-dimensional.
Hope this helps 