In this paper we show that for the D-optimal design, departures from the design are much less important than a departure from the model. As a consequence, we propose, based on D-optimality, a rule for choosing the regression degree. We also study different types of departures from the model to define a new class of D-optimal designs, which is robust and more efficient than the uniform one.
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