When using ADVI, we usually sample the approximation and the using those samples we perform PPC. Consider following example, w = Normal("w", mu = 0, sd = 10, shape = number_of_features) mu = w * x likelihood = Normal("y", mu = mu, std = 10, observed = y) approx = pm.advi.fit(1000) trace = approx.…

Yes, that is conceptually what happen, although the exact sampling happens in the graph. [image] Nadheesh: Moreover, if we want to use intermediate mean and std values using the tracker and then compute the PPC for those values, how can I achieve that? You can set the parameters by doing .se…

Understanding ADVI approx.sample(n)

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Nadheesh April 23, 2018, 6:09am 3

Thanks for the clarification.

It works. Can you please tell me what is the relationship between rho and std?

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Understanding ADVI approx.sample(n)

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