I am trying to identify how to compare models using a non-stationary time series. To add some context, I’m building a hierarchical model where parameters linearly covariate with variables such as time or other physically ones (as an attempt to explain some of the trend pattern), this I call non-stationary model. Then, compare with stationary model.
When model comparing I’ve came across with some concerns regarding the use of future data to test past data (then, the use of LOO). I do not think I have statistical background to replicate the alternative Leave-Future-Out as I haven’t found examples on PyMC3 yet. Is there anything I am missing and LOO/WAIC can be used for time series data if my model built correctly? How to model compare using a non-stationary time series?
I’d appreciate any help and reference indications. Thanks.