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Analysis of supersaturated designs via the Dantzig selector
Authors:Frederick KH Phoa  Yu-Hui PanHongquan Xu
Institution:Department of Statistics, University of California, Los Angeles, CA 90095-1554, USA
Abstract:A supersaturated design is a design whose run size is not enough for estimating all the main effects. It is commonly used in screening experiments, where the goals are to identify sparse and dominant active factors with low cost. In this paper, we study a variable selection method via the Dantzig selector, proposed by Candes and Tao 2007. The Dantzig selector: statistical estimation when pp is much larger than nn. Annals of Statistics 35, 2313–2351], to screen important effects. A graphical procedure and an automated procedure are suggested to accompany with the method. Simulation shows that this method performs well compared to existing methods in the literature and is more efficient at estimating the model size.
Keywords:Primary  62K15  secondary  62J05  62J07
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