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- W2021502484 abstract "Abstract An experimental design is called adaptive if the explanatory variables are chosen successively and at a fixed time the choice may be influenced by the results of the experiments up to that time. Adaptive designs are advantageous in non linear problems, when a good or optimal design depends on the true value of the unknown parameters, to achieve an asymptotically optimal design, but also in linear settings. For the latter case we propose a one-step adaptive design which is locally optimal with respect to all Φ p -criteria, p ≥ 1, and globally superior to nonadaptive designs with respect to the A-criterion." @default.
- W2021502484 created "2016-06-24" @default.
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- W2021502484 date "1990-12-01" @default.
- W2021502484 modified "2023-09-27" @default.
- W2021502484 title "Local optimality and global superiority of adaptive designs in linear models" @default.
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- W2021502484 doi "https://doi.org/10.1016/0167-9473(90)90014-9" @default.
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