On optimal designs for nonlinear models: a general and efficient algorithm

Yang, Min, Biedermann, Stefanie and Tang, Elina (2013) On optimal designs for nonlinear models: a general and efficient algorithm. Journal of the American Statistical Association, 108, (504), 1411-1420. (doi:10.1080/01621459.2013.806268).


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Deriving optimal designs for nonlinear models is challenging in general. Although some recent results allow us to focus on a simple subclass of designs for most problems, deriving a specific optimal design mainly depends on algorithmic approaches. There is need of a general and efficient algorithm which is more broadly applicable than the current state of the art methods. We present a new algorithm that can be used to find optimal designs with respect to a broad class of optimality criteria, when the model parameters or functions thereof are of interest, and for both locally optimal and multi- stage design strategies. We prove convergence to the desired optimal design, and show that the new algorithm outperforms the best available algorithm in various examples

Item Type: Article
Digital Object Identifier (DOI): doi:10.1080/01621459.2013.806268
ISSNs: 0162-1459 (print)
1537-274X (electronic)
Related URLs:
Keywords: convergence, locally optimal design, multi-stage design, \Phi p -optimality
Subjects: H Social Sciences > HA Statistics
Divisions : Faculty of Social and Human Sciences > Mathematical Sciences > Statistics
ePrint ID: 337088
Accepted Date and Publication Date:
Date Deposited: 19 Apr 2012 13:22
Last Modified: 31 Mar 2016 14:26
URI: http://eprints.soton.ac.uk/id/eprint/337088

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