Hello! I am very new to PyMC and bayesian modeling in general. I am currently following some of the example code used in rethinking statistics in chapter 8 and I’m trying to replicate it in PyMC but I am running into dimensionality errors when I am trying to extend my model to a new data set. I saw …

y isn’t a pm.Data in the provided code, so you won’t be able to call set_data on it. You can make a y_data = pm.Data('y_data', df_standard.log_gdp_std, dims=['obs_id']), then pass y_data to set_data. But in general this is a “sharp edge” of PyMC. When doing out of sample prediction, you need to pas…

Using sample posterior predictive on new data

Questions v5

Alexander_Grunewald April 30, 2025, 1:22pm 5

Thank you @jessegrabowski and @Dekermanjian. setting the dummy data for the y worked!

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Using sample posterior predictive on new data

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