F. De Santis, S. Gubbiotti
In Bayesian decision theory, the performance of an action is measured by its posterior expected loss. In some cases it may be convenient/necessary to use a non-optimal decision instead of the optimal one. In these cases it is important to quantify the additional loss we incur and evaluate whether to use the non-optimal decision or not. In this article we study the predictive probability distribution of a relative measure of the additional loss and its use to dene sample size determination criteria in one-sided testing.
Bayesian inference, Experimental design, Exponential family, Predictive analysis, Sample size determination, Statistical decision theory
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