Posterior distribution

In the context of Bayesian statistics, the posterior probability distribution usually describes the epistemic uncertainty about statistical parameters conditional on a collection of observed data. From a given posterior distribution, various point and interval estimates can be derived, such as the maximum a posteriori (MAP) or the highest posterior density interval (HPDI). But while conceptually simple, the posterior distribution is generally not tractable and therefore needs to be either analytically or numerically approximated.