Discussion
Which situation makes a probability of zero dangerous in a model?
Answer: A
A zero prior multiplies to zero whatever the likelihood, so a hypothesis excluded at the outset can never be resurrected by data. That is why smoothing is applied to estimated tables, and why Cromwell's rule advises against certainty. Normalisation still works, sampling is unaffected and no recomputation is forced. The rule matters most where counts are sparse, which in practice is almost everywhere.
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