Some robust design strategies for percentile estimation in binary response models
Some robust design strategies for percentile estimation in binary response models
For the problem of percentile estimation of a quantal response curve, the authors determine multi-objective designs which are robust with respect to misspecifications of the model assumptions. They propose a maximin approach based on efficiencies and provide designs that are simultaneously efficient with respect to the particular choice of various parameter regions and link functions. Furthermore, the authors deal with the problems of designing model and percentile robust experiments and give various examples of such designs,
which are calculated numerically.
Binary response model, robust optimal design, c-efficiency, percentile estimation, multi-objective designs
603-622
Biedermann, Stefanie
fe3027d2-13c3-4d9a-bfef-bcc7c6415039
Dette, Holger
8c7b1c2e-3adc-45df-acfc-9e76509a228e
Pepelyshev, Andrey
136925bf-d2eb-4d4f-998f-48218155ce62
1 December 2006
Biedermann, Stefanie
fe3027d2-13c3-4d9a-bfef-bcc7c6415039
Dette, Holger
8c7b1c2e-3adc-45df-acfc-9e76509a228e
Pepelyshev, Andrey
136925bf-d2eb-4d4f-998f-48218155ce62
Biedermann, Stefanie, Dette, Holger and Pepelyshev, Andrey
(2006)
Some robust design strategies for percentile estimation in binary response models.
Canadian Journal of Statistics, 34 (4), .
Abstract
For the problem of percentile estimation of a quantal response curve, the authors determine multi-objective designs which are robust with respect to misspecifications of the model assumptions. They propose a maximin approach based on efficiencies and provide designs that are simultaneously efficient with respect to the particular choice of various parameter regions and link functions. Furthermore, the authors deal with the problems of designing model and percentile robust experiments and give various examples of such designs,
which are calculated numerically.
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robustdesign.ps
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More information
Published date: 1 December 2006
Keywords:
Binary response model, robust optimal design, c-efficiency, percentile estimation, multi-objective designs
Organisations:
Statistics
Identifiers
Local EPrints ID: 41817
URI: http://eprints.soton.ac.uk/id/eprint/41817
ISSN: 0319-5724
PURE UUID: 055d7927-9317-4efe-8089-fb2fc33f1e8d
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Date deposited: 05 Oct 2006
Last modified: 16 Mar 2024 03:51
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Contributors
Author:
Holger Dette
Author:
Andrey Pepelyshev
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