Dave Yeeles

Bayesian inference · Uncertainty quantification · Model validation

May 3, 2026

What I check before I believe a posterior

A fitted posterior always looks reasonable. That is the problem. It comes out smooth, it has a sensible mode, its credible intervals are the right sort of width, and there is nothing in its appearance that distinguishes a posterior which has correctly characterised your uncertainty from one which is confidently wrong. Fluency is not correctness. If the model is misspecified, the sampler under-converged, or the prior transform quietly different from the prior you intended, you get output that looks exactly the same and means something entirely different.

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