D‐optimal minimax fractional factorial designs
Copyright policy )D‐optimal minimax fractional factorial designs
AbstractThe 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
- Pennsylvania State University United States
- University of Victoria Canada
- University of Victoria Canada
Optimal statistical designs, Factorial statistical designs, Robust parameter designs, annealing algorithm, factorial designs, scale invariance, level permutation, robust designs
Optimal statistical designs, Factorial statistical designs, Robust parameter designs, annealing algorithm, factorial designs, scale invariance, level permutation, robust designs
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