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September, 1989 Very Weak Expansions for Sequentially Designed Experiments: Linear Models
Michael Woodroofe
Ann. Statist. 17(3): 1087-1102 (September, 1989). DOI: 10.1214/aos/1176347257

Abstract

In sequentially designed experiments with linear models, each design variable may depend on previous responses. The use of such sequential designs does not affect the likelihood function or the functional form of the maximum likelihood estimator, but it may affect sampling distributions. In this paper, asymptotic expansions for sampling distributions are obtained. The expansions are very weak ones in which a confidence curve (a function of the unknown parameters) is replaced by a confidence functional defined on a class of prior distributions. The proofs use a version of Stein's identity.

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Michael Woodroofe. "Very Weak Expansions for Sequentially Designed Experiments: Linear Models." Ann. Statist. 17 (3) 1087 - 1102, September, 1989. https://doi.org/10.1214/aos/1176347257

Information

Published: September, 1989
First available in Project Euclid: 12 April 2007

zbMATH: 0683.62039
MathSciNet: MR1015139
Digital Object Identifier: 10.1214/aos/1176347257

Subjects:
Primary: 62E20
Secondary: 62F12, 62L05

Rights: Copyright © 1989 Institute of Mathematical Statistics

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Vol.17 • No. 3 • September, 1989
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