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Robust Designs for Poisson Regression Models

Summary: The authors derive an analytical expression for robust designs for first-order Poisson regression models with uncertainty in the prior parameter estimates. Extending these robust designs and using the authors' methodology produces results with comparable estimates to existing models in less time. The methodology is also applied to cases where the linear predictor contains uncertainty and explored as an alternative to computationally intense methods in problems such as screening experiments.

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  • Topics: Statistics
  • Keywords: Analytical methods, Canonical analysis, Estimation, Linear models, Optimal design, Poisson distribution, Screening, Unknown parameters
  • Author: McGree, James M.; Eccleston, John A.
  • Journal: Technometrics