How to use the posterior distribution of one model as a prior distribution for another model

[Yamaguchi]

@Simon @jessegrabowski @iavicenna

Thank you for your quick response. All the content is very informative!!

@jessegrabowski
I found an example of using histogram_approximation in a previous thread.
What is the difference between histogram_approximation and a multivariate normal approximation?
Would I use histogram_approximation to approximate a discrete distribution?

How best to use a posterior sample as a prior for a future integration in another model?

Hi @jessegrabowski, thanks for the links. Have I understood the histogram_approximation method right that you could do something like: import pymc as pm import pymc_experimental as pmx import pytensor.tensor as pt import arviz with modelA: a = pm.Normal('a') b = pm.Normal('b') obs = pm.Normal('obs', a + b, obs_error, observed=obs_mean) traceA = pm.sample() postA = arviz.extract(traceA.posterior) postA_ab = np.stack([postA["a"], postA["b"]]) with modelB: a = pm.Uniform('a…