Optimum design theory improves experimental outcomes using models and strategies for both qualitative and quantitative factors.
Part I. Fundamentals Introduction Some key ideas Experimental strategies The choice of a model Models and least squares Criteria for a good experiment Standard designs The analysis of experiments Part II. Theory and applications Optimum design theory Criteria of optimality Experiments with both qualitative and quantitative factors Blocking response surface designs Restricted region designs Failure of the experiment and design augmentation Non-linear models Optimum Bayesian design Discrimination between models Composite design criteria Further topics.
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Wheeler et al. (1993) studied this question.
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