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Optimal Experimental Design

Design of experiments (DOE) is a part of statistics that provides tools for efficient experimentation. A model-oriented view, where some knowledge about the form of the data-generating process is assumed, naturally leads to the so-called optimum experimental design (OED). Although the subject started in an agricultural context, it is nowadays being applied in many areas, both in science and in industry. Any relevant design of experiments problem may fit this track. Models used in practice in many areas such as pharmaceutical industries, agriculture, engineering, medicine, among others are very much welcome. The contributions have to include a significant computational element.

Jesus Lopez-Fidalgo, University of Castilla-La Mancha, Spain.
Anthony C. Atkinson, London School of Economics, UK
Kalliopi Mylona, University of Southampton, UK
Organized Sessions associated with this Track