Supersaturated designs: are our results significant?

DOI10.1016/j.csda.2011.03.015zbMath1464.62063OpenAlexW1984776583MaRDI QIDQ1658317

Robert W. Mee, David J. Edwards

Publication date: 14 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2011.03.015

zbMATH Keywords

randomization testshrinkage methodsadjusted \(p\)-valueeffect sparsityall-subsets regressionglobal model test

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Factorial statistical designs (62K15)

Related Items (4)

Augmenting supersaturated designs with Bayesian \(D\)-optimality ⋮ Screening active factors in supersaturated designs ⋮ Supersaturated designs: a review of their construction and analysis ⋮ On the analysis of unbalanced two-level supersaturated designs via generalized linear models

Cites Work

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• Analysis of supersaturated designs via the Dantzig selector
• Least angle regression. (With discussion)
• Asymptotic-power problems in the analysis of supersaturated designs
• 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).
• An Analysis for Unreplicated Fractional Factorials
• Some Systematic Supersaturated Designs
• An empirical comparison of permutation methods for tests of partial regression coefficients in a linear model
• Construction of supersaturated designs through partially aliased interactions
• Permutation Tests for Linear Models
• Generating Systematic Supersaturated Designs

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