Abstract
In this work we focus on saturated D-optimal designs. Using a recent result in Fontana et al. (J Stat Plann Inference 147:204–211, 2014), we identify D-optimal designs with the solutions of an optimization problem with linear constraints where the objective function to be maximized is the determinant of the information matrix. We study the possibility to replace the determinant of the information matrix with simpler objective functions that could give the same optimal solutions. These new objective functions are based on the geometric structure of the design. We perform a simulation study. In all the test cases we observe that designs with high values of D-efficiency have also high values of the new objective functions.
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Fontana, R., Rapallo, F., Rogantin, M.P. (2014). D-optimal Saturated Designs: A Simulation Study. In: Melas, V., Mignani, S., Monari, P., Salmaso, L. (eds) Topics in Statistical Simulation. Springer Proceedings in Mathematics & Statistics, vol 114. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2104-1_17
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DOI: https://doi.org/10.1007/978-1-4939-2104-1_17
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