DeepLabCut SARIMAX parameters

I am using DeepLabCut to track some very small animals (a few pixels) in a large, heterogenous lighting environment. I am trying to use the ARIMA filter to see if the autoregressive model can help filter out false positives (other small, non-animal particles that don’t demonstrate such predictive movement). However, I’m not familiar with the model parameters (ARdegree, MAdegree) and I’m curious if there’s a way in deeplabcut to determine what the best model values should be. I do not have an a priori estimate of what the ARdegree should be, and I imagine that this value can change for a given dataset. Is there a way for DLC to output the AR and MA terms/plots (as from here) to help better estimate what these values should be?

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Dear @Nicholai_Hensley ,

The meaning of the AR, MA parameters is discussed here:

The best way to find the best parameters would be to cross validate them. Unfortunately, there is currently no built in option to cross-validate the parameters. However, you could run

for various parameter settings of ARdegree & MAdegree and look at the stats of the models. The easiest way to do this would be to edit

which is used for fitting (for each body part) and then also extract the stats from the fitted models:
if you pass disp=True you get all kinds of statistics trom the sarimax class