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December, 1983 General Differential and Lagrangian Theory for Optimal Experimental Design
F. Pukelsheim, D. M. Titterington
Ann. Statist. 11(4): 1060-1068 (December, 1983). DOI: 10.1214/aos/1176346321

Abstract

The problem of optimal experimental design for estimating parameters in linear regression models is placed in a general convex analysis setting. Duality results are obtained using two approaches, one based on subgradients and the other on Lagrangian theory. The subgradient concept is also used to derive a potentially useful equivalence theorm for establishing the optimality of a singular design and, finally, general versions of the original equivalence theorems of Kiefer and Wolfowitz (1960) are obtained.

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F. Pukelsheim. D. M. Titterington. "General Differential and Lagrangian Theory for Optimal Experimental Design." Ann. Statist. 11 (4) 1060 - 1068, December, 1983. https://doi.org/10.1214/aos/1176346321

Information

Published: December, 1983
First available in Project Euclid: 12 April 2007

zbMATH: 0592.62066
MathSciNet: MR865345
Digital Object Identifier: 10.1214/aos/1176346321

Subjects:
Primary: 62K05
Secondary: 90C25

Rights: Copyright © 1983 Institute of Mathematical Statistics

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Vol.11 • No. 4 • December, 1983
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