D-optimum designs in multi-factor models with heteroscedastic errors

This paper considers the construction of D-optimum designs for Kronecker product and additive regression models when the errors are heteroscedastic. Sufficient conditions are given so that D-optimum designs for the multi-factor models can be built from D-optimum designs for their sub-models with a single factor. A robustness study is included to investigate how design efficiencies change when the efficiency functions are miss-specified.