There are many other ways of defining Bayesian estimations and credal intervals for \(\theta\) on the basis of the posterior density. The specific type of estimation that the Bayesian analysis offers can be determined by the demands of the scientist. Any Bayesian estimation will to some extent resemble the maximum likelihood estimator due to the central role of the likelihoods in the Bayesian formalism. However, the output will also depend on the prior probability over the hypotheses, and generally speaking it will only tend to the maximum likelihood estimator when the sample size tends to infinity. See  Section 4.2.2  for more on this so-called “washing out” of the priors. 