Using posterior as likelihood

I think the current approach is to use pymc.Interpolated — PyMC 4.3.0+0.gea721e4a.dirty documentation

Basically create a random variable using the posterior samples (the smoothed histogram of the marginal posterior distribution), it might not work well especially the posterior is highly correlated

1 Like