## The Annals of Statistics

### Saturated locally optimal designs under differentiable optimality criteria

#### 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.

#### Article information

Source
Ann. Statist., Volume 43, Number 1 (2015), 30-56.

Dates
First available in Project Euclid: 18 November 2014

https://projecteuclid.org/euclid.aos/1416322035

Digital Object Identifier
doi:10.1214/14-AOS1263

Mathematical Reviews number (MathSciNet)
MR3285599

Zentralblatt MATH identifier
1321.62097

Subjects
Primary: 62K05: Optimal designs
Secondary: 62J02: General nonlinear regression

#### Citation

Hu, Linwei; Yang, Min; Stufken, John. Saturated locally optimal designs under differentiable optimality criteria. Ann. Statist. 43 (2015), no. 1, 30--56. doi:10.1214/14-AOS1263. https://projecteuclid.org/euclid.aos/1416322035

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