Expected Information as Expected Utility

Expected Information as Expected Utility

The normative procedure for the design of an experiment is to select a utility function, assess the probabilities, and to choose that design of maximum expected utility. One difficulty with this view is that a scientist typically does not have, nor can be normally expected to have, a clear idea of t...

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Veröffentlicht in:The Annals of Statistics. - Institute of Mathematical Statistics. - 7(1979), 3, Seite 686-690
1. Verfasser: Bernardo, José M. (VerfasserIn)
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 1979
Zugriff auf das übergeordnete Werk:The Annals of Statistics
Schlagworte:Bayesian statistics decision theory design of experiments information scientific inference utility Economics Philosophy Physical sciences Behavioral sciences Mathematics
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520 |a The normative procedure for the design of an experiment is to select a utility function, assess the probabilities, and to choose that design of maximum expected utility. One difficulty with this view is that a scientist typically does not have, nor can be normally expected to have, a clear idea of the utility of his results. An alternative is to design an experiment to maximize the expected information to be gained from it. In this paper we show that the latter view is a special case of the former with an appropriate choice of the decision space and a reasonable constraint on the utility function. In particular, the Shannon concept of information is seen to play a more important role in experimental design than was hitherto thought possible. 
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