A two-stage variable selection strategy for supersaturated designs with multiple responses

DOI10.1007/S11464-012-0255-9zbMath1458.62181OpenAlexW2044607881MaRDI QIDQ372243

Min-Qian Liu, Qiaozhen Zhang, Yuhui Yin

Publication date: 14 October 2013

Published in: Frontiers of Mathematics in China (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11464-012-0255-9

zbMATH Keywords

stepwise regressionMPLSmultivariate partial least squaresSSDvariable importance in projections

Mathematics Subject Classification ID

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

Related Items (4)

Functionally induced priors for componentwise Gibbs sampler in the analysis of supersaturated designs ⋮ Construction of supersaturated design with large number of factors by the complementary design method ⋮ Acceleration of the stochastic search variable selection via componentwise Gibbs sampling ⋮ A method for augmenting supersaturated designs

Cites Work

• Unnamed Item
• Unnamed Item
• Construction of equidistant and weak equidistant supersaturated designs
• On construction of optimal mixed-level supersaturated designs
• Construction of optimal supersaturated design with large number of levels
• PLS generalised linear regression
• Modelling by supersaturated designs
• Analysis of supersaturated designs via the Dantzig selector
• Optimal mixed-level supersaturated design
• Data analysis in supersaturated designs.
• A method for screening active effects in supersaturated designs
• A cluster analysis selection strategy for supersaturated designs
• A comparison of design and model selection methods for supersaturated experiments
• An Analysis for Unreplicated Fractional Factorials
• 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

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