Asymptotics take on a different meaning in the Bayesian estimation context, since parameters do not ?converge? to a population quantity. Nonetheless, in a Bayesian estimation setting, as the sample size increases, the likelihood function will dominate the posterior density. What does this imply about the Bayesian ?estimator? when this occurs?
This question was answered on: Jul 11, 2017
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