Bias Vs. Variance
From the late 1950’s to up to the later 1970’s a debate ensued in the Statistics community between two schools of thought in experimental design. The main point of contention was the practical utility of optimal experimental design theory, mainly developed by J. Kiefer and co-workers. We will refer to this school as the “optimal design school” in this chapter. As mentioned in Section 5.7, using optimality theory one designs an experiment that is optimal in some precisely defined way for a given model form; the design will not be optimal, and probably, not even “robust” if the true process obeys a model different than the assumed one. This point of view is held by G. Box and his co-workers, which we will refer here as the “Applied Statistics school”. The purpose of the present chapter is to introduce the main ideas behind this debate. Since very few practical conclusions resulted from the debate itself, the chapter is necessarily short (the methods developed by both schools have had a great impact, but that is the matter for the other chapters in this book).
KeywordsPolynomial Model Assumed Model Mixture Experiment Variance Debate True Process
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