No this is not Pareto-k warning. Diagnostic for WAIC is described in the section 2.2 of Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. See paragraph starting “The effective number of parameters”. This diagnostic is not as good as Pareto k , and I often think that maybe we should compute Pareto k also in case when people try to compute WAIC.
Yes, but that is not the value you want to know! That value is overoptimistic.
It means you should not trust your estimates and you should use loo instead. Sometimes loo works, when WAIC fails, but sometimes they both fail, but at least loo gives better diagnostic.
I guess you have error how you do the computations, but since I haven’t seen your code I’m not able to tell you why this happens.
I think you have mixed things, as this doesn’t make sense. If you want me to be able to help you, please show the code.
That I can confirm, that you can’t trust the results.