Saturated locally optimal designs under differentiable optimality criteria

H. U. Linwei; Min Yang; John Stufken

doi:10.1214/14-AOS1263

Saturated locally optimal designs under differentiable optimality criteria

H. U. Linwei, Min Yang, John Stufken

CLAS-NS: Mathematics and Statistical Sciences, School of (SMSS)

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3 Scopus citations

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 language	English (US)
Pages (from-to)	30-56
Number of pages	27
Journal	Annals of Statistics
Volume	43
Issue number	1
DOIs	https://doi.org/10.1214/14-AOS1263
Publication status	Published - Feb 1 2015

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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

Linwei, H. U., Yang, M., & Stufken, J. (2015). Saturated locally optimal designs under differentiable optimality criteria. Annals of Statistics, 43(1), 30-56. https://doi.org/10.1214/14-AOS1263

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10.1214/14-AOS1263