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Abstract The sampling distributions of various Bayesian point estimators are examined and it is shown that by choosing an appropriate prior distribution for the unknown parameter such estimators can be less biased than the maximum likelihood estimator. It is also shown that a pivotal quantity can be developed by a suitable transformation of the unknown parameter.
Joanes et al. (Sat,) studied this question.