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April 2001 Maximin designs for exponential growth models and heteroscedastic polynomial models
Lorens A. Imhof
Ann. Statist. 29(2): 561-576 (April 2001). DOI: 10.1214/aos/1009210553


This paper is concerned with nonsequential optimal designs for a class of nonlinear growth models, which includes the asymptotic regression model. This design problem is intimately related to the problem of finding optimal designs for polynomial regression models with only partially known heteroscedastic structure. In each case, a straightforward application of the usual D­optimality criterion would lead to designs which depend on the unknown underlying parameters. To overcome this undesirable dependence a maximin approach is adopted. The theorem of Perron and Frobenius on primitive matrices plays a crucial role in the analysis.


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Lorens A. Imhof. "Maximin designs for exponential growth models and heteroscedastic polynomial models." Ann. Statist. 29 (2) 561 - 576, April 2001.


Published: April 2001
First available in Project Euclid: 24 December 2001

zbMATH: 1012.62081
MathSciNet: MR1863970
Digital Object Identifier: 10.1214/aos/1009210553

Primary: 62K05

Keywords: approximate design , maximin criterion , Nonlinear design problem , standardized criterion

Rights: Copyright © 2001 Institute of Mathematical Statistics


Vol.29 • No. 2 • April 2001
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