Optimal designs for generalized non-linear models with application to second-harmonic generation experiments


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), 281-299. (doi:10.1111/j.1467-9876.2010.00749.x).

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Description/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

Item Type: Article
ISSNs: 0035-9254 (print)
1467-9876 (electronic)
Keywords: bayesian design, cluster design, d-optimality, laser–surface chemistry, non-linear regression, poisson regression
Subjects: H Social Sciences > HA Statistics
Q Science > QA Mathematics
Divisions: University Structure - Pre August 2011 > School of Mathematics > Statistics
University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
ePrint ID: 180917
Date Deposited: 14 Apr 2011 14:49
Last Modified: 28 Mar 2014 15:20
Projects:
PLATFORM: End-to-End pipeline for chemical information: from the laboratory to literature and back again
Funded by: EPSRC (EP/C008863/1)
April 2005 to June 2010
URI: http://eprints.soton.ac.uk/id/eprint/180917

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