Interpret plot_trace from PYMC New to Bayesian Modeling and the python library PYMC. Got some confusing result. How would an expert on Bayesian modeling interpret these graphs?
with BVAR_model:
    trace = pm.sample(chains=4, random_seed=rng)

az.plot_trace(trace)


After changing the number of lags, from 2 to 4, and applied differencing I got the following result. The right hand side looks better, but the left hand side confuses, strange distribution.


Those trace plots don't link right. They should look like “hairy, fat caterpillars” i.e. something like the below.

Moreover, they should heave the same means, while on your plots we can clearly see different chains getting stuck at different values. It might suggest that your model is misspecified and theatre are identifability issues, by the folk theorem of statistical computing.
