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Title
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A mixed integer optimization approach for model selection in screening experiments
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Author
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Abstract
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| After completing the experimental runs of a screening design, the responses under study are analyzed by statistical methods to detect the active effects. To increase the chances of correctly identifying these effects, a good analysis method should provide alternative interpretations of the data, reveal the aliasing present in the design, and search only meaningful sets of effects as defined by user-specified restrictions such as effect heredity. This article presents a mixed integer optimization strategy to analyze data from screening designs that possesses all these properties. We illustrate our method by analyzing data from real and synthetic experiments, and using simulations. |
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Language
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English
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Source (journal)
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Journal of quality technology / American Society for Quality Control. - Milwaukee, Wis., 1969, currens
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Publication
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Philadelphia
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Taylor & francis inc
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2020
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ISSN
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0022-4065
[print]
2575-6230
[online]
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DOI
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10.1080/00224065.2020.1712275
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Volume/pages
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p. 1-24
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ISI
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000518560400001
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Full text (Publisher's DOI)
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