ABSTRACT
One view of the development of the Empirical Bayes (EB) approach is that it is an attractive compromise between the classical non-Bayes and the full Bayes approaches to statistical inference. These represent extremes where the former uses no prior information whereas the latter requires complete specification of a prior distribution. The EB approach uses previous data to get an estimate of the prior distribution. The EB method is actually only one of several methods of effective utilization of data from such a two-stage sampling scheme. Established competitors of the EB method are compound decision theory, the full Bayesian multiparameter approach and a modified likelihood approach. It is another alternative to EB techniques which is regarded as a stimulus for the creation of the EB approach. The applicability of compound estimators has been the source of controversy since the appearance of the original James-Stein estimator. Hence, EB method which does not use loss functions is practically identical to the likelihood-based methods.
