Abstract
Search designs form an important class of experimental designs that allow the identifying of the true model, consisting of a set of factorial effects, among many. Most of the work in this field has been made in the cases where there are at most one or two two-factor interaction effects considered nonnegligible. This article focuses on model identification through the use of search linear models containing, apart from the general mean and the main effects, up to five nonnegligible two-factor interaction effects. The new search designs are based exclusively on orthogonal arrays.
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Acknowledgments
The authors thank two anonymous referees for their valuable comments and suggestions that led to a significant improvement of this article.
Notes
Dedicated with great respect to Jagdish N. Srivastava.