Applied Optimal Designs
There are constantly new and continuing applications of optimal design ideas in different fields. An impetus behind this driving force is the ever-increasing cost of running experiments or field projects. A well-designed study cannot be overemphasized because a carefully designed study can provide accurate statistical inference with minimum cost. Optimum design of experiments is therefore an important subfield in statistics. This book is a collection of papers on applications of optimal designs to real problems in selected fields. Some chapters include an overview of applications of optimal design in specific fields. Because optimal design ideas are widely used in many disciplines and researchers have different backgrounds, we have tried to make this book accessible to our readers by minimizing the technical discussion. Our purpose here is to expose researchers to applications of optimal design in various fields and hope that in so doing we will stimulate further work in optimal experimental designs. In the next few paragraphs, we provide a sample of applications of optimal design theory in different fields.
Optimal design theory has been frequently applied to engineering (Gianchandani and Crary, 1998; Crary et al., 2000; Crary 2002), chemical engineering (Atkinson and Bogacka, 1997), and calibration problems (Cook and Nachtsheim, 1982). Optimal design theory has also been applied to the design of electronic products. For example, Clyde et al. (1995) used Bayesian optimal design strategies for constructing heart defibrillators. In bioengineering, Lutchen and Saidel (1982) derived an optimal design for nonlinear pulmonary models that described mechanical and gas concentration dynamics during a tracer gas washout. Nathanson and Saidel (1985) also constructed an optimal design for a ferrokinetics experiment. Beginning in the late 1990s, applications of optimal designs are being increasingly used in food engineering (Cunha et al., 1997, 1998; Cunha and Oliverira, 2000).
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