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Cyan comments on Are calibration and rational decisions mutually exclusive? (Part one) - Less Wrong
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Comments (19)
Gibbs sampling and EM aren't relevant to the ideas of this post.
Neither Gibbs sampling nor EM is intrinsically Bayesian or frequentist. EM is just a maximization algorithm useful for certain special cases; the maximized function could be a likelihood or a posterior density. Gibbs sampling is just a MCMC algorithm; usually the target distribution is a Bayesian posterior distribution, but it doesn't have to be.
You said, "seek a prior that guarantees posterior calibration." That's what both EM and Gibbs sampling do, which is why I asked.
You and I have very different understandings of what EM and Gibbs sampling accomplish. Do you have references for your point of view?