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Originally published in 1970; with a second edition in 1989.
Empirical Bayes methods use some of the apparatus of the pure Bayes
approach, but an actual prior distribution is assumed to generate
the data sequence. It can be estimated thus producing empirical
Bayes estimates or decision rules. In this second edition, details
are provided of the derivation and the performance of empirical
Bayes rules for a variety of special models. Attention is given to
the problem of assessing the goodness of an empirical Bayes
estimator for a given set of prior data. Chapters also focus on
alternatives to the empirical Bayes approach and actual
applications of empirical Bayes methods.
Originally published in 1970; with a second edition in 1989.
Empirical Bayes methods use some of the apparatus of the pure Bayes
approach, but an actual prior distribution is assumed to generate
the data sequence. It can be estimated thus producing empirical
Bayes estimates or decision rules. In this second edition, details
are provided of the derivation and the performance of empirical
Bayes rules for a variety of special models. Attention is given to
the problem of assessing the goodness of an empirical Bayes
estimator for a given set of prior data. Chapters also focus on
alternatives to the empirical Bayes approach and actual
applications of empirical Bayes methods.
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