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- W2418069332 abstract "ABSTRACTA supersaturated design (SSD) is a design whose run size is not enough for estimating all main effects. Such a design is commonly used in screening experiments to screen active effects based on the effect sparsity principle. Traditional approaches, such as the ordinary stepwise regression and the best subset variable selection, may not be appropriate in this situation. In this article, a new variable selection method is proposed based on the idea of staged dimensionality reduction. Simulations and several real data studies indicate that the newly proposed method is more effective than the existing data analysis methods." @default.
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- W2418069332 date "2016-12-18" @default.
- W2418069332 modified "2023-09-27" @default.
- W2418069332 title "A three-stage variable selection method for supersaturated designs" @default.
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- W2418069332 doi "https://doi.org/10.1080/03610918.2015.1053927" @default.
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