Model-Robust and Model-Discriminating Designs

Event Details
  • Date/Time:
    • Tuesday February 26, 2008 - Wednesday February 27, 2008
      10:00 am - 10:59 am
  • Location: Executive Classroom, Main ISyE Building
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Xiaoming Huo
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Summary Sentence: Model-Robust and Model-Discriminating Designs

Full Summary: Professor William Li, Operations and Management Science Department, University of Minnesota will present a lecture on model-robust and model-discrimination design.

Title: Model-Robust and Model-Discriminating Designs

Guest Lecturer: Professor William Li
Operations and Management Science Department
University of Minnesota

Presentation Abstract: We discuss the problem of designing an experiment for selecting a good model from a set of models of interest. The research is built on the work on model-robust design of Li and Nachtsheim (2000) and model-discriminating designs of Jones, Li, Nachtsheim, and Ye (2007, 2008). We introduce new criteria for model discrimination and use these and existing criteria to evaluate standard orthogonal designs. We also use these criteria to construct optimal two-level designs for screening experiments. Results indicate that, for a given sample size and number of desired factors, not all orthogonal designs are model-discriminating designs for the model spaces considered. We conclude with some simulation studies, which show that the proposed designs can lead to a higher probability of identifying the correct model in the data analysis procedure than traditional minimum aberration designs.

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School of Industrial and Systems Engineering (ISYE)

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model-discrimination design, model-robust
  • Created By: Barbara Christopher
  • Workflow Status: Published
  • Created On: Oct 12, 2009 - 5:20pm
  • Last Updated: Oct 7, 2016 - 9:47pm