A Variable Selection Method for Analyzing Supersaturated Designs

DOI10.1080/03610918.2010.546540zbMath1217.62117OpenAlexW2131958747MaRDI QIDQ3015861

A. Skountzou, Kalliopi Mylona, Christos Koukouvinos

Publication date: 13 July 2011

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2010.546540

zbMATH Keywords

tablesvariable selectioninformation criteriabest subset method

Mathematics Subject Classification ID

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

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Sure independence screening for analyzing supersaturated designs

Cites Work

• A hybrid SAGA algorithm for the construction of \(E(s^2)\)-optimal cyclic supersaturated designs
• Analysis of supersaturated designs via the Dantzig selector
• Estimating the dimension of a model
• Construction of \(E(s^2)\) optimal supersaturated designs using cyclic BIBDs
• Data analysis in supersaturated designs.
• \(E(s^{2})\)-optimal supersaturated designs with good minimax properties
• \(E(s^{2})\)-optimal and minimax-optimal cyclic supersaturated designs via multi-objective simulated annealing
• Fitting autoregressive models for prediction
• An Algorithmic Approach to Constructing Supersaturated Designs
• An Analysis for Unreplicated Fractional Factorials
• A Biometrics Invited Paper. The Analysis and Selection of Variables in Linear Regression
• A method for constructing supersaturated designs and its Es² optimality
• A Bayesian Variable-Selection Approach for Analyzing Designed Experiments with Complex Aliasing
• Generating Systematic Supersaturated Designs
• A Method for Analyzing Supersaturated Designs with a Block Orthogonal Structure