Abstract
Many industrial experiments involve some factors whose levels are harder to set than others. The best way to deal with these is to plan the experiment carefully as a split-plot, or more generally a multistratum, design. Several different approaches for constructing split-plot type response surface designs have been proposed in the literature since 2001, which has allowed experimenters to make better use of their resources by using more efficient designs than the classical balanced ones. One of these approaches, the stratum-by-stratum strategy has been shown to produce designs that are less efficient than locally D-optimal designs. An improved stratum-by-stratum algorithm is given, which, though more computationally intensive than the old one, makes better use of the advantages of this approach, that is, it can be used for any structure and does not depend on prior estimates of the variance components. This is shown to be almost as good as the locally optimal designs in terms of their own criteria and more robust across a range of criteria. Supplementary materials for this article are available online.
| Original language | English |
|---|---|
| Pages (from-to) | 145-154 |
| Number of pages | 10 |
| Journal | TECHNOMETRICS |
| Volume | 57 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 3 Apr 2015 |
Keywords
- A-optimality
- D-optimality
- Hard-to-change factor
- Hard-to-set factor
- Mixed model
- Prediction variance
- Response surface