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We develop general theory for finding locally optimal designs in a class of single-covariate models under any differentiable optimality criterion. Yang and Stufken [Ann. Statist. 40 (2012) 1665–1681] and Dette

We develop general theory for finding locally optimal designs in a class of single-covariate models under any differentiable optimality criterion. Yang and Stufken [Ann. Statist. 40 (2012) 1665–1681] and Dette and Schorning [Ann. Statist. 41 (2013) 1260–1267] gave complete class results for optimal designs under such models. Based on their results, saturated optimal designs exist; however, how to find such designs has not been addressed. We develop tools to find saturated optimal designs, and also prove their uniqueness under mild conditions.

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Date Created
  • 2015-02-01
Resource Type
  • Text
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    Identifier
    • Digital object identifier: 10.1214/14-AOS1263
    • Identifier Type
      International standard serial number
      Identifier Value
      0090-5364
    • Identifier Type
      International standard serial number
      Identifier Value
      2168-8966

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    Hu, Linwei, Yang, Min, & Stufken, John (2015). SATURATED LOCALLY OPTIMAL DESIGNS UNDER DIFFERENTIABLE OPTIMALITY CRITERIA. ANNALS OF STATISTICS, 43(1), 30-56. http://dx.doi.org/10.1214/14-AOS1263

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