I am new to PyMC so this may be a silly question. Say I have height and age data from School A. I use this to model in PyMC the linear relationship between age and height. I also have age data for one class from School B. I use this to generate a model of the distribution of the mean age in the cl…

I think I’ve built what I was after - you can put it all in one model! Here is what I ended up with: import numpy as np from pymc3 import Normal, Model, HalfCauchy, sample schoolA_age_obs = np.array([-0.016, 0.002, -0.028, 0.072, -0.02 , 0.02 , 0.054, -0.054, -0.002, 0.07 , 0.008, 0.…

Combining the outputs from two models trained using different data

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lucianopaz January 25, 2019, 2:40pm 2

It sounds like you could use a GLM. You fit the regression with school A and do posterior predictive on school B

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Combining the outputs from two models trained using different data

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