A method for screening active effects in supersaturated designs |
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Authors: | Qiao-Zhen Zhang Run-Chu ZhangMin-Qian Liu |
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Institution: | Department of Statistics, School of Mathematical Sciences and LPMC, Nankai University, Tianjin 300071, China |
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Abstract: | A supersaturated design (SSD) is a design whose run size is not enough for estimating all the main effects. The goal in conducting such a design is to identify, presumably only a few, relatively dominant active effects with a cost as low as possible. However, data analysis of such designs remains primitive: traditional approaches are not appropriate in such a situation and several methods which were proposed in the literature in recent years are effective when used to analyze two-level SSDs. In this paper, we introduce a variable selection procedure, called the PLSVS method, to screen active effects in mixed-level SSDs based on the variable importance in projection which is an important concept in the partial least-squares regression. Simulation studies show that this procedure is effective. |
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Keywords: | Primary 62K15 secondary 62J05 |
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