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- W2093164755 abstract "Assume k independent populations are given which are distributed according to Qϑ1, …, Qϑk. Taking samples of size n the population with the largest ϑ-value is to be selected. For the sequence of models localized at ϑ0 and any sequence of selection rules an asymptotic upper bound is derived for the minimum probability of correct selection in the indifference zone approach. Asymptotically optimal selection rules are constructed using the central sequence of the sequence of experiments and by substituting ϑ0 by an √n-consistent estimator. In the semiparametric location model f(x − ϑ) with unknown density f an asymptotically optimum selection rule is constructed where the score function −f′f is estimated by kernel estimators." @default.
- W2093164755 created "2016-06-24" @default.
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- W2093164755 date "1996-09-01" @default.
- W2093164755 modified "2023-09-23" @default.
- W2093164755 title "Adaptive selection of the best population" @default.
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- W2093164755 doi "https://doi.org/10.1016/0378-3758(95)00171-9" @default.
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