Robust optimal designs refer to a class of experimental designs that are specifically constructed to be effective under a variety of conditions and assumptions. They aim to maintain their statistical efficiency even when there are deviations from the assumed model or parameters, making them particularly valuable in real-world scenarios where uncertainty and variability are prevalent.
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