Optimal experiment design for nonlinear models subject to large prior uncertainties.

@article{Walter1987OptimalED,
  title={Optimal experiment design for nonlinear models subject to large prior uncertainties.},
  author={Eric Walter and Luc Pronzato},
  journal={The American journal of physiology},
  year={1987},
  volume={253 3 Pt 2},
  pages={R530-4}
}
Classical experiment design generally yields an experiment that depends on the value of the parameters to be estimated, which are, of course, unknown. Assuming that the model parameters belong to a population with known statistics, we propose to take the a priori parameter uncertainty into account by optimizing the mathematical expectation of a functional of the Fisher information matrix. This optimization is performed with a stochastic approximation algorithm that makes robust experiment… CONTINUE READING

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