Optimal designs for generalized non-linear models with application to second-harmonic generation experiments
Optimal designs for generalized non-linear models with application to second-harmonic generation experiments
The design of experiments for generalized non-linear models is investigated and applied to an optical process for characterizing interfaces which is widely used in the physical and natural sciences. Design strategies for overcoming the dependence of a D-optimal design on the values of the model parameters are explored, including the use of Bayesian designs. Designs for the accurate estimation of model parameters are presented and compared, as are designs for the estimation of a set of ratios of parameters which is of particular importance in the motivating example. The effectiveness of various design methods is studied, and the benefits of well-designed experiments are demonstrated
bayesian design, cluster design, d-optimality, laser–surface chemistry, non-linear regression, poisson regression
281-299
Biedermann, Stefanie
fe3027d2-13c3-4d9a-bfef-bcc7c6415039
Woods, David C.
ae21f7e2-29d9-4f55-98a2-639c5e44c79c
March 2011
Biedermann, Stefanie
fe3027d2-13c3-4d9a-bfef-bcc7c6415039
Woods, David C.
ae21f7e2-29d9-4f55-98a2-639c5e44c79c
Biedermann, Stefanie and Woods, David C.
(2011)
Optimal designs for generalized non-linear models with application to second-harmonic generation experiments.
Journal of the Royal Statistical Society, Series C (Applied Statistics), 60 (2), .
(doi:10.1111/j.1467-9876.2010.00749.x).
Abstract
The design of experiments for generalized non-linear models is investigated and applied to an optical process for characterizing interfaces which is widely used in the physical and natural sciences. Design strategies for overcoming the dependence of a D-optimal design on the values of the model parameters are explored, including the use of Bayesian designs. Designs for the accurate estimation of model parameters are presented and compared, as are designs for the estimation of a set of ratios of parameters which is of particular importance in the motivating example. The effectiveness of various design methods is studied, and the benefits of well-designed experiments are demonstrated
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Published date: March 2011
Keywords:
bayesian design, cluster design, d-optimality, laser–surface chemistry, non-linear regression, poisson regression
Organisations:
Statistics, Southampton Statistical Research Inst.
Identifiers
Local EPrints ID: 180917
URI: http://eprints.soton.ac.uk/id/eprint/180917
ISSN: 0035-9254
PURE UUID: 07e153d1-555e-48ae-b2a6-3b7bb85ed82a
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Date deposited: 14 Apr 2011 14:49
Last modified: 15 Mar 2024 03:26
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