Hello! I am trying to do a simple multivariate regression using bayesian modeling. I am using real data from a CSV table. I am able to set up the model and sample from posterior, but I am confused with how to actually generate new predictions from new Xi data. My training data have one Y (output) …

You can use set_data() to swap out the data you used for inference for something new (e.g., out-of-sample test data) before running sample_posterior_predictive. That will allow you to use your estimated model parameters to generate predictions about your outcome (i.e., Y in your case) in a new scen…

How do I predict on new, unseen real data using pm.sample_posterior_predictive?

Questions

cluhmann January 7, 2021, 12:20am 14

A pandas dataframe? Something like this should work:

    pm.set_data( {'my_observed_variable': df['my_column'].to_numpy()} )

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How do I predict on new, unseen real data using pm.sample_posterior_predictive?

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