Posterior predictive distribution
In statistics, and especially Bayesian statistics, the posterior predictive distribution is the distribution of unobserved observations (prediction) conditional on the observed data. Described as the distribution that a new i.i.d. data point would have, given a set of N existing i.i.d. observations
. In a frequentist context, this might be derived by computing the maximum likelihood estimate (or some other estimate) of the parameter(s) given the observed data, and then plugging them into the distribution function of the new observations.