Abstract
For some experimenters, a disadvantage of the standard optimal design approach is that it does not consider explicitly the aliasing of specified model terms with terms that are potentially important but are not included in the model. For example, when constructing an optimal design for a first-order model, aliasing of main effects and interactions is not considered. This can lead to designs that are optimal for estimation of the primary effects of interest, yet have undesirable aliasing structures. In this article, we construct exact designs that minimize the squared norm of the alias matrix subject to constraints on design efficiency. We demonstrate use of the method for the construction of screening and response surface designs.
Original language | English (US) |
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Pages (from-to) | 62-71 |
Number of pages | 10 |
Journal | Technometrics |
Volume | 53 |
Issue number | 1 |
DOIs | |
State | Published - Feb 1 2011 |
Keywords
- Alias matrix
- Bayesian design
- Constrained design
- D-optimality
- Minimum bias design
- Response surface design