Comments (3)
That's very cool! I didn't know there was a nice diagnostic for how "good" variational approximations are. Just wondering if this could be a nice contribution to arviz itself so the method can also be used for other inference frameworks, e.g., Stan?
from numpyro.
There is a method in arviz (arviz.stats.stats._psislw()
) which calculates the test statistic given the log importance ratios. But to calculate the log importance ratios you need the numpyro model, guide, best fit parameters, and the samples that you're trying to evaluate, thus my suggestion for a new method that would do this all in one go.
from numpyro.
Do you know if it's possible to evaluate those other quantities from the arviz InferenceData
object?
from numpyro.
Related Issues (20)
- [FR] Truncated Power Law distribution
- An auto guide's `_unpack_latent` and `_unpack_latent._inverse` don't use produce the same order HOT 1
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from numpyro.