A method for screening active effects in supersaturated designs

DOI10.1016/j.jspi.2006.06.038zbMath1118.62080OpenAlexW2069409332MaRDI QIDQ2370487

Min-Qian Liu, Qiaozhen Zhang, Run-Chu Zhang

Publication date: 26 June 2007

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2006.06.038

zbMATH Keywords

variable selectionmixed-levelpartial least-squaresvariable importance in projection

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Factorial statistical designs (62K15)

Related Items (16)

Screening active factors in supersaturated designs ⋮ Construction of supersaturated design with large number of factors by the complementary design method ⋮ A two-stage variable selection strategy for supersaturated designs with multiple responses ⋮ Construction of optimal supersaturated design with large number of levels ⋮ Construction of equidistant and weak equidistant supersaturated designs ⋮ A cluster analysis selection strategy for supersaturated designs ⋮ Optimal mixed-level \(k\)-circulant supersaturated designs ⋮ Acceleration of the stochastic search variable selection via componentwise Gibbs sampling ⋮ An algorithm for constructing mixed-level \(k\)-circulant supersaturated designs ⋮ Analyzing supersaturated designs for discrete responses via generalized linear models ⋮ The effects of nonnormality on the analysis of supersaturated designs: a comparison of stepwise, SCAD and permutation test methods ⋮ On construction of optimal mixed-level supersaturated designs ⋮ A screening approach for non-parametric global sensitivity analysis ⋮ A method for augmenting supersaturated designs ⋮ Two-level supersaturated designs: a review ⋮ Construction of efficient mixed-level \(k\)-circulant supersaturated designs

Cites Work

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• PLS generalised linear regression
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• Optimal mixed-level supersaturated design
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• Data analysis in supersaturated designs.
• Some Systematic Supersaturated Designs
• An Interpretation of Partial Least Squares
• A Bayesian Variable-Selection Approach for Analyzing Designed Experiments with Complex Aliasing
• The Peculiar Shrinkage Properties of Partial Least Squares Regression
• Generating Systematic Supersaturated Designs
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