Prior as data, prior as belief, prior as soft constraint, prior as unconditional distribution in a generative model

In Bayesian inference, the prior density is this thing that you multiply to the likelihood to get the unnormalized posterior distribution. For the purpose of inference conditional on the data, the prior is the prior is the prior, and where … Continue reading → …