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D‐optimal minimax fractional factorial designs
Authors:Dennis K J Lin  Julie Zhou
Institution:1. Department of Statistics, Pennsylvania State University, University Park, PA, USA;2. Department of Mathematics and Statistics, University of Victoria, 3800 Finnerty Road, Victoria, British Columbia, Canada V8W 3R4
Abstract:The D‐optimal minimax criterion is proposed to construct fractional factorial designs. The resulting designs are very efficient, and robust against misspecification of the effects in the linear model. The criterion was first proposed by Wilmut & Zhou (2011); their work is limited to two‐level factorial designs, however. In this paper we extend this criterion to designs with factors having any levels (including mixed levels) and explore several important properties of this criterion. Theoretical results are obtained for construction of fractional factorial designs in general. This minimax criterion is not only scale invariant, but also invariant under level permutations. Moreover, it can be applied to any run size. This is an advantage over some other existing criteria. The Canadian Journal of Statistics 41: 325–340; 2013 © 2013 Statistical Society of Canada
Keywords:Annealing algorithm  factorial design  level permutation  robust design  scale invariance  MSC 2010: Primary 62K05  secondary 62K15
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