On the empirical Bayes approach to multiple decision problems with sequential components |
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Authors: | R. J. Karunamuni |
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Affiliation: | (1) Department of Sttistics and Apphed Probability, University of Alberta, 434 Central Academic Building, T6G 2G1 Edmonton, Alberta, Canada |
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Abstract: | The empirical Bayes approach to multiple decision problems with a sequential decision problem as the component is studied. An empirical Bayesm-truncated sequential decision procedure is exhibited for general multiple decision problems. With a sequential component, an empirical Bayes sequential decision procedure selects both a stopping rule function and a terminal decision rule function for use in the component. Asymptotic results are presented for the convergence of the Bayes risk of the empirical Bayes sequential decision procedure. |
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Keywords: | Empirical Bayes procedures asymptotic risk equivalence asymptotic superiority sequential components multiple decision problems |
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