Adaptive Full Factorial Experiment
An adaptive full factorial experiment is an experimental design that starts with a complete crossing of all factors and all their levels, then uses interim data to modify subsequent runs — dropping unpromising factor levels, adding new ones, or re-allocating replication — while preserving the full factorial structure within each phase. This integration of full factorial coverage with adaptive decision rules allows researchers to explore all main effects and interactions without committing to a fixed, inefficient run plan before any data are observed.
Rekod sumber
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- Atkinson, A., Donev, A., & Tobias, R. (2007). Optimum Experimental Designs, with SAS. Oxford University Press. · ISBN 978-0199296606
- Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. · ISBN 978-1119113478
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