freedman-1965-bvm-countable-failure

Summary

Freedman showed that the standard reassurance linking Bayesian and frequentist inference, namely that the posterior eventually locks onto the true distribution, is not a universal law. In probability spaces with countably infinite outcomes, the Bayesian estimate can keep missing the target even with infinite data, so the system cannot treat convergence as a guaranteed property in those settings.