Abstract
In Section 19 we dealt with general decision problems of the form \( \bar{{\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{D}}} = (I,D,V) \)= (I,D,V), where I: = (ΩI,AI) and D: = (ΩD,AD) denoted measurable spaces and V a set of separately measurable functions on ΩI × ΩD. From now on, and for the remainder of the chapter, we shall specialize the general framework in two steps: First we shall restrict our attention to decision problems of the form <Inline>2</Inline>k(I): = (I,Dk,V) with Dk: = {1,…,k} (k ≥1) as the decision space and the set V of all bounded, separately measurable functions on ΩI × ΩD as the set of loss functions. Later we shall consider decision problems of the form \( {\bar{{\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{D}}}_k}\,(I): = (I,{D_k},V) \)k (In) with In = {l, …, n} (n ≥ 1).
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© 1982 Springer-Verlag New York Inc.
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Heyer, H. (1982). Comparison of Finite Experiments. In: Theory of Statistical Experiments. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-8218-8_9
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DOI: https://doi.org/10.1007/978-1-4613-8218-8_9
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4613-8220-1
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