AISM 53, 418-426
© 2001 ISM
(Received July 21, 1998; revised August 17, 1999)
Abstract. This paper examines the construction of optimal designs when one assumes a homoscedastic linear model, but the underlying model is heteroscedastic. A criterion that takes this type of misspecification into account is formulated and an equivalence theorem is given. We also provide explicit optimal designs for single-factor and multi-factor experiments under various heteroscedastic assumptions and discuss the relationship between the D-optimal design sought here and the conventional D-optimal design.
Key words and phrases: Heteroscedasticity, D-optimal, efficiency function, equivalence theorem, mean squared error, L-optimal, multi-factor experiment.
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