Strategies for Supersaturated Screening: Group Orthogonal and Constrained Var(s) Designs
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Publication:6631901
DOI10.1080/00401706.2020.1850529MaRDI QIDQ6631901
Byran J. Smucker, David Edwards, Maria L. Weese, Jonathan W. Stallrich
Publication date: 1 November 2024
Published in: Technometrics (Search for Journal in Brave)
Cites Work
- Supersaturated designs: a review of their construction and analysis
- Model-robust supersaturated and partially supersaturated designs
- Analysis of supersaturated designs via the Dantzig selector
- Augmenting supersaturated designs with Bayesian \(D\)-optimality
- Supersaturated designs robust to two-factor interactions
- A comparison of design and model selection methods for supersaturated experiments
- The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
- Bayesian D-optimal supersaturated designs
- Some Systematic Supersaturated Designs
- Construction of supersaturated designs through partially aliased interactions
- Optimal Supersaturated Designs
- Sure independence screening for analyzing supersaturated designs
- Controlling Variable Selection by the Addition of Pseudovariables
- Screening
- Construction, Properties, and Analysis of Group-Orthogonal Supersaturated Designs
Related Items (2)
Factor selection in screening experiments by aggregation over random models ⋮ Selection of Two-Level Supersaturated Designs for Main Effects Models
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