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Planning Herbicide Dose-Response Bioassays Using the Bootstrap

  • Silvio Sandoval Zocchi
  • Clarice Garcia Borges Demétrio
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 51)

Abstract

Dose response herbicide bioassays generally demand large amounts of time and resources. The choice of doses to be used is thus critical. For a given model, optimum design theory can be used to generate optimum designs for parameter estimation. However, such designs depend on the parameter values and in general do not have enough support points to detect lack of fit. This work describes the use of bootstrap methods to generate an empirical distribution of the optimum design points, based on the results of a previous experiment, and suggests designs based on this distribution. These designs are then compared to the Bayesian D-optimum designs

Keywords

D-optimum designs Bayesian D-optimum designs Bootstrap Non-linear models Dose-response models 

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Copyright information

© Springer Science+Business Media Dordrecht 2001

Authors and Affiliations

  • Silvio Sandoval Zocchi
    • 1
  • Clarice Garcia Borges Demétrio
    • 1
  1. 1.Departamento de Ciências Exatas, ESALQUniversity of São PauloPiracicabaBrazil

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