I’m still relatively new to pymc. When using arviz.compare
or arviz.loo
for the pymc gaussian process model I get the warning:
Estimated shape parameter of Pareto distribution is greater than 0.7 for one or more samples. You should consider using a more robust model, this is because importance sampling is less likely to work well if the marginal posterior and LOO posterior are very different. This is more likely to happen with a non-robust model and highly influential observations.
What exactly would constitute a more robust model here. Any help is appreciated. Thank you.