Analysis of supersaturated designs via the Dantzig selector

作者：Phoa Frederick K H; Pan Yu Hui; Xu Hongquan^*

来源：Journal of Statistical Planning and Inference, 2009, 139(7): 2362-2372.

DOI：10.1016/j.jspi.2008.10.023

• Akaike information criterion
• Dantzig selector
• Factor sparsity
• Linear programming
• Profile plot
• Screening experiment
• Supersaturated design

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 p is much larger than n. 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.

• 出版日期2009-7-1