@article{Bischoff_2016, title={D-optimally Lack-of-Fit-Test-efficient Designs and Related Simple Designs}, volume={37}, url={https://ajs.or.at/index.php/ajs/article/view/vol37%2C%20no3%264%20-%203}, DOI={10.17713/ajs.v37i3&4.306}, abstractNote={In practice it is often more popular to use a uniform than an optimal design for estimating the unknown parameters of a linear regression model. The reason is that the model can be checked by a uniform design but it cannot be checked by an optimal design in many cases. On the other hand, however, for important regression models a uniform design is not very efficient to estimate the unknown parameters. Therefore Bischoff and Miller<br />proposed in a series of papers a compromise. It is suggested there to look for designs that are optimal with respect to a specific criterion in the class of designs that are efficient for lack-of-fit-tests. In this paper we consider the D-criterion and polynomial regression models. For polynomial regression models with degree larger than two D-optimally lack-of-fit-test-efficient designs are difficult to determine. Therefore, in this paper we determine easily to calculate and for estimating the parameters highly efficient designs that are<br />additionally lack-of-fit-testâ€“efficient.<br /><br />}, number={3&4}, journal={Austrian Journal of Statistics}, author={Bischoff, Wolfgang}, year={2016}, month={Apr.}, pages={245â€“253} }