Optimal experimental designs for inverse quadratic regression models

In this paper optimal experimental designs for inverse quadratic regression models are determined. We consider two difierent parameterizations of the model and investigate local optimal designs with respect to the c-, D- and E-criteria, which re∞ect various aspects of the precision of the maximum likelihood estimator for the parameters in inverse quadratic regression models. In particular it is demonstrated that for a su‐ciently large design space geometric allocation rules are optimal with respect to many optimality criteria. Moreover, in numerous cases the designs with respect to the difierent criteria are supported at the same points. Finally, the e‐ciencies of difierent optimal designs with respect to various optimality criteria are studied, and the e‐ciency of some commonly used designs are investigated.