Hi I am new to numpyro.
I use numpyro and the NUTS sampler to train several 1000 of models using historical data for say a year worth of data each. As this takes many hours I’d like to know how to know the best practice about persisting the model say to a pickle file. I use the posterior and the model. Then at a later date when new data has accumulated to reload the model and posterior and use it as a prior for training the model using the new data.
In this and later steps can I/should I skip the warm up step ?
Is there some recommended metric/diagnostic to estimate if the the new data’s drift from the prior distribution.