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 results are 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.
clustering, locally optimal design, log-linear models, robust design
721-730
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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April 2009
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.
(2009)
D-optimal designs for Poisson regression models.
Statistica Sinica, 19 (2), .
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 results are 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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Published date: April 2009
Keywords:
clustering, locally optimal design, log-linear models, robust design
Organisations:
Southampton Statistical Research Inst.
Identifiers
Local EPrints ID: 151269
URI: http://eprints.soton.ac.uk/id/eprint/151269
ISSN: 1017-0405
PURE UUID: bcd75157-ed34-40ba-9d2a-457cb13876a3
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Date deposited: 10 May 2010 10:29
Last modified: 14 Mar 2024 02:44
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Contributors
Author:
K.G. Russell
Author:
S.M. Lewis
Author:
J.A. Eccleston
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