Some problems of statistical prediction

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Abstract
A general framework is introduced for the study of inference and decision predictions about the outcome of a future experiment from the data of an independent informative experiment. This allows a simple classification of prediction problems, and shows the place of standard inference predictions within the framework. A Bayesian approach to decision prediction is then presented and techniques appropriate to a variety of realistic utility functions are developed. Finally, some prediction problems associated with classes of experiments are considered.

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