4.5 Article

Maximum One-Factor-At-A-Time Designs for Screening in Computer Experiments

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Article Statistics & Probability

Maximum One-Factor-At-A-Time Designs for Screening in Computer Experiments

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Summary: This article explores the difficult problem of identifying important factors from a large number of potentially important factors in a highly nonlinear and computationally expensive black box model. By establishing a connection between Morris screening and Sobol' design, an improved design called MOFAT is developed for screening, along with efficient methods for constructing MOFAT designs with a large number of factors.

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