A comparison of design and model selection methods for supersaturated experiments
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References listed on IDEAS
- S. M. Lewis & A. M. Dean, 2001. "Detection of interactions in experiments on large numbers of factors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(4), pages 633-672.
- Li, Runze & Lin, Dennis K. J., 2002. "Data analysis in supersaturated designs," Statistics & Probability Letters, Elsevier, vol. 59(2), pages 135-144, September.
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Cited by:
- Singh, Rakhi & Stufken, John, 2024. "Factor selection in screening experiments by aggregation over random models," Computational Statistics & Data Analysis, Elsevier, vol. 194(C).
- VÁZQUEZ-ALCOCER, Alan & SCHOEN, Eric D. & GOOS, Peter, 2018. "A mixed integer optimization approach for model selection in screening experiments," Working Papers 2018007, University of Antwerp, Faculty of Business and Economics.
- Bradley Jones & Dibyen Majumdar, 2014. "Optimal Supersaturated Designs," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1592-1600, December.
- Edwards, David J. & Mee, Robert W., 2011. "Supersaturated designs: Are our results significant?," Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2652-2664, September.
- Das, Ujjwal & Gupta, Sudhir & Gupta, Shuva, 2014. "Screening active factors in supersaturated designs," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 223-232.
- N. Balakrishnan & C. Koukouvinos & C. Parpoula, 2015. "Analyzing supersaturated designs for discrete responses via generalized linear models," Statistical Papers, Springer, vol. 56(1), pages 121-145, February.
- Gutman, Alex J. & White, Edward D. & Lin, Dennis K.J. & Hill, Raymond R., 2014. "Augmenting supersaturated designs with Bayesian D-optimality," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1147-1158.
- Crabbe, M. & Vandebroek, M., 2012. "Improving the efficiency of individualized designs for the mixed logit choice model by including covariates," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2059-2072.
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Keywords
Bayesian D-optimal designs E(s2)-optimal designs Effect sparsity Gauss-Dantzig selector Main effects Screening Simulation;Statistics
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