D-optimal designs for Poisson regression models
D-optimal designs for Poisson regression models
We consider the problem of finding an optimal design under a Poisson regression model with a log link, any number of independent variables and an additive linear predictor. Local D-optimality of a class of designs is established through use of a canonical form of the problem and a general equivalence theorem. The theorem is applied in conjunction with clustering techniques to obtain a fast method of finding designs that are robust to wide ranges of model parameter values. The methods are illustrated through examples.
Southampton Statistical Sciences Research Institute, University of Southampton
Russell, K.G.
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Woods, D.C.
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Lewis, S.M.
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Eccleston, J.A.
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29 January 2008
Russell, K.G.
7a489c0a-13d2-4432-98c1-373692512949
Woods, D.C.
ae21f7e2-29d9-4f55-98a2-639c5e44c79c
Lewis, S.M.
a69a3245-8c19-41c6-bf46-0b3b02d83cb8
Eccleston, J.A.
8d0ae072-0870-4302-a54d-af9ec88e42b8
Russell, K.G., Woods, D.C., Lewis, S.M. and Eccleston, J.A.
(2008)
D-optimal designs for Poisson regression models
(S3RI Methodology Working Papers, M08/01)
Southampton, UK.
Southampton Statistical Sciences Research Institute, University of Southampton
11pp.
Record type:
Monograph
(Working Paper)
Abstract
We consider the problem of finding an optimal design under a Poisson regression model with a log link, any number of independent variables and an additive linear predictor. Local D-optimality of a class of designs is established through use of a canonical form of the problem and a general equivalence theorem. The theorem is applied in conjunction with clustering techniques to obtain a fast method of finding designs that are robust to wide ranges of model parameter values. The methods are illustrated through examples.
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50282-01.pdf
- Author's Original
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Published date: 29 January 2008
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Local EPrints ID: 50282
URI: http://eprints.soton.ac.uk/id/eprint/50282
PURE UUID: 19e36e68-77f5-400e-a772-11934d169ec7
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Date deposited: 12 Feb 2008
Last modified: 16 Mar 2024 03:14
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Contributors
Author:
K.G. Russell
Author:
S.M. Lewis
Author:
J.A. Eccleston
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