Designing Experiments for Nonlinear Models - An Introduction
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Authors
Johnson, Rachel T.
Montgomery, Douglas C.
Subjects
optimal design
factorial design
Bayesian D-optimal
factorial design
Bayesian D-optimal
Advisors
Date of Issue
2009-08
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Abstract
We illustrate the construction of Bayesian D-optimal designs for nonlinear models and compare the relative efficiency
of standard designs with these designs for several models and prior distributions on the parameters. Through a
relative efficiency analysis, we show that standard designs can perform well in situations where the nonlinear model
is intrinsically linear. However, if the model is nonlinear and its expectation function cannot be linearized by simple
transformations, the nonlinear optimal design is considerably more efficient than the standard design.
Type
Article
Description
The article of record as published may be found at http://dx.doi.org/10.1002/qre.1063
Series/Report No
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Citation
Quality and Reliability Engineering International, Volume 26, pp. 431-441, 2009
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.