= Prior elicitation
Translate external information into a <prior distribution> by asking for representative values, uncertainty intervals and tail probabilities. Fit parameters of a suitable distribution to those judgments and inspect the resulting <prior predictive distribution>. For a probability believed near $0.1$, a <beta distribution> with parameters $0.1\kappa,0.9\kappa$ has the desired mean; its concentration $\kappa$ can be chosen to match a stated probability of exceeding $0.15$. The words “near” and “unlikely” alone do not specify one unique prior.
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