Robust designs for poisson regression models

McGree, James M. and Eccleston, John A. (2012) Robust designs for poisson regression models. Technometrics, 54 1: 64-72. doi:10.1080/00401706.2012.648867

Author McGree, James M.
Eccleston, John A.
Title Robust designs for poisson regression models
Journal name Technometrics   Check publisher's open access policy
ISSN 0040-1706
Publication date 2012-02
Year available 2011
Sub-type Article (original research)
DOI 10.1080/00401706.2012.648867
Volume 54
Issue 1
Start page 64
End page 72
Total pages 9
Place of publication Baltimore, MD, United States
Publisher American Statistical Association
Collection year 2013
Language eng
Abstract We consider the problem of how to construct robust designs for Poisson regression models. An analytical expression is derived for robust designs for first-order Poisson regression models where uncertainty exists in the prior parameter estimates.Given certain constraints in themethodology, itmay be necessary to extend the robust designs for implementation in practical experiments. With these extensions, our methodology constructs designs that perform similarly, in terms of estimation, to current techniques and offers the solution in a more timely manner.We further apply this analytic result to cases where uncertainty exists in the linear predictor. The application of this methodology to practical design problems such as screening experiments is explored. Given the minimal prior knowledge that is usually available when conducting such experiments, it is recommended to derive designs robust across a variety of systems. However, incorporating such uncertainty into the design process can be a computationally intense exercise. Hence, our analytic approach is explored as an alternative.
Keyword Analytical solution
Average model
Canonical form
Compromise design
Generalized linear model
Optimal design
Generalized Linear-Models
Nonlinear Models
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Available online: 20 December 2011.

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
Official 2013 Collection
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