At most we should ascribe a prior probability of zero and then do some Bayesian updating to get a posterior.
I think you’d have to call that “Bayesian not-updating”. If your priors include 0 or 1 those beliefs will not change through Bayesian updating.
The prior is P(A), which we have said is 0. The posterior is P(A|B), which happens to be a fraction with 0 as the numerator!
I get it.
I think you’d have to call that “Bayesian not-updating”. If your priors include 0 or 1 those beliefs will not change through Bayesian updating.
The prior is P(A), which we have said is 0. The posterior is P(A|B), which happens to be a fraction with 0 as the numerator!
I get it.