Saturated locally optimal designs under differentiable optimality criteria

H. U. Linwei, Min Yang, John Stufken

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

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
Volume43
Issue number1
DOIs
StatePublished - Feb 1 2015

Fingerprint

Locally Optimal Design
Optimality Criteria
Saturated Design
Differentiable
Covariates
Uniqueness
Model
Optimality
Class

Keywords

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

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

Saturated locally optimal designs under differentiable optimality criteria. / Linwei, H. U.; Yang, Min; Stufken, John.

In: Annals of Statistics, Vol. 43, No. 1, 01.02.2015, p. 30-56.

Research output: Contribution to journalArticle

Linwei, H. U. ; Yang, Min ; Stufken, John. / Saturated locally optimal designs under differentiable optimality criteria. In: Annals of Statistics. 2015 ; Vol. 43, No. 1. pp. 30-56.
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