Saturated locally optimal designs under differentiable optimality criteria

H. U. Linwei, Min Yang, John Stufken

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)30-56
Number of pages27
JournalAnnals of Statistics
Issue number1
StatePublished - Feb 1 2015


  • Chebyshev system
  • Complete class
  • Generalized linear model
  • Locally optimal design
  • Nonlinear model

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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