Description

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

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.

Downloads
PDF (211.9 KB)

Details

Title
  • Saturated Locally Optimal Designs Under Differentiable Optimality Criteria
Contributors
Date Created
2015-02-01
Resource Type
  • Text
  • Collections this item is in
    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

    Citation and reuse

    Cite this item

    This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.

    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

    Machine-readable links